"""Data Analysis and Visualization"""
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
import numpy as np
import missingno
"""Machine Learning"""
from sklearn.linear_model import LinearRegression
from sklearn.metrics import r2_score, explained_variance_score, mean_absolute_error, mean_squared_error
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout
from tensorflow.keras.constraints import MinMaxNorm
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
"""General and Styling"""
import os.path
import warnings
warnings.filterwarnings("ignore")
plt.style.use('ggplot') #matplotlib style options
plt.rcParams['figure.figsize'] = (15, 8) #matplotlib style options
from functions import *
data = pd.read_csv('Comprehensive IMDb Data.csv')
display_missingno(data)
data2 = display_genre_avg_score(data)
Romance average score: 6.58
Thriller average score: 5.9
Comedy average score: 6.19
Fantasy average score: 6.03
Drama average score: 6.71
Western average score: 5.95
Action average score: 6.24
Family average score: 6.67
Sci-Fi average score: 6.35
Biography average score: 7.1
Mystery average score: 6.81
Horror average score: 5.84
Crime average score: 6.7
Animation average score: 6.7
Adventure average score: 6.29
display_budget_avg_score(data2)
average score for budget 0 to 10,000.0$ : 7.1
average score for budget 10,000.0 to 100,000.0$ : 6.92
average score for budget 100,000.0 to 1,000,000.0$ : 6.48
average score for budget 1,000,000.0 to 10,000,000.0$ : 6.43
average score for budget 10,000,000.0 to 100,000,000.0$ : 6.35
average score for budget 100,000,000.0 to 1,000,000,000.0$ : 6.68
display_general_plots(data2)
data2.corr()
data = change_dataset(data)
final_movie_dataset = oscar_wins_nominations(data)
Data have already been extracted!
Data have already been extracted!
violin_plot(final_movie_dataset)
kde_plots(final_movie_dataset)
plot1_1(final_movie_dataset)
plot1_2(final_movie_dataset)
plot1_3(final_movie_dataset)
plot1_4(final_movie_dataset)
plot1_5(final_movie_dataset)
plot1_6(final_movie_dataset)
plot1_7(final_movie_dataset)
plot1_8(final_movie_dataset)
plot1_9(final_movie_dataset)
plot1_10(final_movie_dataset)
plot_correlation(final_movie_dataset)
X, Y = gross_feature_engineering(final_movie_dataset)
X_train, X_validation, Y_train, Y_validation = standardize_and_train_LR(X, Y)
3961 samples to train on and 1321 to validate the final model on (unseen data)
The r2 score is: 0.62
The mean absolut error score is: 66697123.71
The mean squared error score is: 118732971.83
standardize_and_train_NN(X_train, X_validation, Y_train, Y_validation)
Epoch 1/10
31/31 [==============================] - 1s 2ms/step - loss: 41604681134243840.0000 - mean_absolute_error: 101297085.7500
Epoch 2/10
31/31 [==============================] - 0s 2ms/step - loss: 32331803859615744.0000 - mean_absolute_error: 80942750.7500
Epoch 3/10
31/31 [==============================] - 0s 2ms/step - loss: 18547379288408064.0000 - mean_absolute_error: 73798528.7500
Epoch 4/10
31/31 [==============================] - 0s 3ms/step - loss: 16583603353812992.0000 - mean_absolute_error: 66835423.6250
Epoch 5/10
31/31 [==============================] - 0s 3ms/step - loss: 18275943294435328.0000 - mean_absolute_error: 67471177.8750
Epoch 6/10
31/31 [==============================] - 0s 3ms/step - loss: 17945269568012288.0000 - mean_absolute_error: 70269613.6250
Epoch 7/10
31/31 [==============================] - 0s 2ms/step - loss: 15395392279543808.0000 - mean_absolute_error: 65688986.5000
Epoch 8/10
31/31 [==============================] - 0s 3ms/step - loss: 18234691005972480.0000 - mean_absolute_error: 72992477.2500
Epoch 9/10
31/31 [==============================] - 0s 3ms/step - loss: 16127602867568640.0000 - mean_absolute_error: 65416894.3750
Epoch 10/10
31/31 [==============================] - 0s 2ms/step - loss: 14229047504535552.0000 - mean_absolute_error: 64732426.8750
The r2 score is: 0.56
The mean absolut error score is: 67863293.20
The mean squared error score is: 126948771.47
X, Y = score_feature_engineering(final_movie_dataset)
X_train, X_validation, Y_train, Y_validation = standardize_and_train_LR_score(X, Y)
3961 samples to train on and 1321 to validate the final model on (unseen data)
The r2 score is: 0.36
The mean absolut error score is: 0.59
The mean squared error score is: 0.78
history = standardize_and_train_NN_score(X, Y)
Epoch 1/300
28/28 [==============================] - 1s 29ms/step - loss: 65.0289 - mean_absolute_error: 6.5135 - val_loss: 20.6522 - val_mean_absolute_error: 4.4453
Epoch 2/300
28/28 [==============================] - 0s 4ms/step - loss: 18.6309 - mean_absolute_error: 3.4910 - val_loss: 7.9597 - val_mean_absolute_error: 2.6894
Epoch 3/300
28/28 [==============================] - 0s 3ms/step - loss: 12.8346 - mean_absolute_error: 2.8749 - val_loss: 6.0136 - val_mean_absolute_error: 2.3063
Epoch 4/300
28/28 [==============================] - 0s 4ms/step - loss: 9.7005 - mean_absolute_error: 2.4716 - val_loss: 5.6561 - val_mean_absolute_error: 2.2330
Epoch 5/300
28/28 [==============================] - 0s 3ms/step - loss: 8.7034 - mean_absolute_error: 2.3354 - val_loss: 6.1085 - val_mean_absolute_error: 2.3306
Epoch 6/300
28/28 [==============================] - 0s 3ms/step - loss: 8.1089 - mean_absolute_error: 2.2507 - val_loss: 5.7391 - val_mean_absolute_error: 2.2526
Epoch 7/300
28/28 [==============================] - 0s 4ms/step - loss: 7.9485 - mean_absolute_error: 2.2279 - val_loss: 4.8309 - val_mean_absolute_error: 2.0429
Epoch 8/300
28/28 [==============================] - 0s 4ms/step - loss: 7.1101 - mean_absolute_error: 2.1015 - val_loss: 4.7481 - val_mean_absolute_error: 2.0216
Epoch 9/300
28/28 [==============================] - 0s 4ms/step - loss: 6.9499 - mean_absolute_error: 2.0819 - val_loss: 4.6931 - val_mean_absolute_error: 2.0071
Epoch 10/300
28/28 [==============================] - 0s 3ms/step - loss: 6.3745 - mean_absolute_error: 2.0062 - val_loss: 4.6667 - val_mean_absolute_error: 2.0018
Epoch 11/300
28/28 [==============================] - 0s 5ms/step - loss: 6.2572 - mean_absolute_error: 1.9542 - val_loss: 4.1365 - val_mean_absolute_error: 1.8664
Epoch 12/300
28/28 [==============================] - 0s 3ms/step - loss: 5.9999 - mean_absolute_error: 1.9368 - val_loss: 4.4571 - val_mean_absolute_error: 1.9505
Epoch 13/300
28/28 [==============================] - 0s 4ms/step - loss: 5.9692 - mean_absolute_error: 1.9179 - val_loss: 3.7432 - val_mean_absolute_error: 1.7611
Epoch 14/300
28/28 [==============================] - 0s 3ms/step - loss: 5.9964 - mean_absolute_error: 1.9469 - val_loss: 3.6863 - val_mean_absolute_error: 1.7470
Epoch 15/300
28/28 [==============================] - 0s 3ms/step - loss: 5.5310 - mean_absolute_error: 1.8774 - val_loss: 3.7893 - val_mean_absolute_error: 1.7775
Epoch 16/300
28/28 [==============================] - 0s 4ms/step - loss: 5.4458 - mean_absolute_error: 1.8542 - val_loss: 4.1468 - val_mean_absolute_error: 1.8755
Epoch 17/300
28/28 [==============================] - 0s 5ms/step - loss: 5.6529 - mean_absolute_error: 1.9066 - val_loss: 3.4038 - val_mean_absolute_error: 1.6700
Epoch 18/300
28/28 [==============================] - 0s 4ms/step - loss: 5.2103 - mean_absolute_error: 1.8124 - val_loss: 3.9424 - val_mean_absolute_error: 1.8230
Epoch 19/300
28/28 [==============================] - 0s 3ms/step - loss: 4.8168 - mean_absolute_error: 1.7400 - val_loss: 2.9871 - val_mean_absolute_error: 1.5475
Epoch 20/300
28/28 [==============================] - 0s 4ms/step - loss: 4.6212 - mean_absolute_error: 1.7007 - val_loss: 3.5093 - val_mean_absolute_error: 1.7049
Epoch 21/300
28/28 [==============================] - 0s 3ms/step - loss: 4.6076 - mean_absolute_error: 1.7105 - val_loss: 3.0894 - val_mean_absolute_error: 1.5818
Epoch 22/300
28/28 [==============================] - 0s 3ms/step - loss: 4.1584 - mean_absolute_error: 1.6108 - val_loss: 2.9679 - val_mean_absolute_error: 1.5447
Epoch 23/300
28/28 [==============================] - 0s 3ms/step - loss: 4.2515 - mean_absolute_error: 1.6315 - val_loss: 3.8365 - val_mean_absolute_error: 1.7982
Epoch 24/300
28/28 [==============================] - 0s 3ms/step - loss: 4.3022 - mean_absolute_error: 1.6462 - val_loss: 3.1979 - val_mean_absolute_error: 1.6176
Epoch 25/300
28/28 [==============================] - 0s 3ms/step - loss: 4.1146 - mean_absolute_error: 1.6046 - val_loss: 3.5544 - val_mean_absolute_error: 1.7219
Epoch 26/300
28/28 [==============================] - 0s 3ms/step - loss: 4.1750 - mean_absolute_error: 1.6272 - val_loss: 3.5493 - val_mean_absolute_error: 1.7211
Epoch 27/300
28/28 [==============================] - 0s 5ms/step - loss: 4.0719 - mean_absolute_error: 1.5975 - val_loss: 3.6507 - val_mean_absolute_error: 1.7503
Epoch 28/300
28/28 [==============================] - 0s 5ms/step - loss: 4.0710 - mean_absolute_error: 1.6033 - val_loss: 3.4520 - val_mean_absolute_error: 1.6948
Epoch 29/300
28/28 [==============================] - 0s 3ms/step - loss: 3.8860 - mean_absolute_error: 1.5763 - val_loss: 3.5599 - val_mean_absolute_error: 1.7260
Epoch 30/300
28/28 [==============================] - 0s 4ms/step - loss: 3.8216 - mean_absolute_error: 1.5467 - val_loss: 3.2503 - val_mean_absolute_error: 1.6375
Epoch 31/300
28/28 [==============================] - 0s 3ms/step - loss: 3.8192 - mean_absolute_error: 1.5443 - val_loss: 3.0341 - val_mean_absolute_error: 1.5699
Epoch 32/300
28/28 [==============================] - 0s 3ms/step - loss: 3.7523 - mean_absolute_error: 1.5367 - val_loss: 3.5789 - val_mean_absolute_error: 1.7325
Epoch 33/300
28/28 [==============================] - 0s 3ms/step - loss: 3.7031 - mean_absolute_error: 1.5224 - val_loss: 3.3522 - val_mean_absolute_error: 1.6648
Epoch 34/300
28/28 [==============================] - 0s 3ms/step - loss: 3.7550 - mean_absolute_error: 1.5385 - val_loss: 3.5469 - val_mean_absolute_error: 1.7248
Epoch 35/300
28/28 [==============================] - 0s 4ms/step - loss: 3.4255 - mean_absolute_error: 1.4764 - val_loss: 3.0934 - val_mean_absolute_error: 1.5909
Epoch 36/300
28/28 [==============================] - 0s 5ms/step - loss: 3.6547 - mean_absolute_error: 1.5055 - val_loss: 3.1560 - val_mean_absolute_error: 1.6102
Epoch 37/300
28/28 [==============================] - 0s 5ms/step - loss: 3.5814 - mean_absolute_error: 1.5121 - val_loss: 3.3766 - val_mean_absolute_error: 1.6770
Epoch 38/300
28/28 [==============================] - 0s 3ms/step - loss: 3.3248 - mean_absolute_error: 1.4329 - val_loss: 2.7612 - val_mean_absolute_error: 1.4906
Epoch 39/300
28/28 [==============================] - 0s 3ms/step - loss: 3.1825 - mean_absolute_error: 1.4174 - val_loss: 2.8368 - val_mean_absolute_error: 1.5158
Epoch 40/300
28/28 [==============================] - 0s 5ms/step - loss: 3.4398 - mean_absolute_error: 1.4758 - val_loss: 2.6606 - val_mean_absolute_error: 1.4589
Epoch 41/300
28/28 [==============================] - 0s 3ms/step - loss: 3.1956 - mean_absolute_error: 1.4261 - val_loss: 2.6707 - val_mean_absolute_error: 1.4632
Epoch 42/300
28/28 [==============================] - 0s 3ms/step - loss: 3.1611 - mean_absolute_error: 1.4138 - val_loss: 2.7113 - val_mean_absolute_error: 1.4778
Epoch 43/300
28/28 [==============================] - 0s 5ms/step - loss: 3.1414 - mean_absolute_error: 1.3980 - val_loss: 3.1124 - val_mean_absolute_error: 1.6027
Epoch 44/300
28/28 [==============================] - 0s 3ms/step - loss: 3.0469 - mean_absolute_error: 1.3942 - val_loss: 2.8980 - val_mean_absolute_error: 1.5381
Epoch 45/300
28/28 [==============================] - 0s 4ms/step - loss: 3.0248 - mean_absolute_error: 1.3792 - val_loss: 2.6238 - val_mean_absolute_error: 1.4519
Epoch 46/300
28/28 [==============================] - 0s 5ms/step - loss: 2.9132 - mean_absolute_error: 1.3606 - val_loss: 2.2042 - val_mean_absolute_error: 1.3114
Epoch 47/300
28/28 [==============================] - 0s 3ms/step - loss: 3.0402 - mean_absolute_error: 1.3750 - val_loss: 2.4899 - val_mean_absolute_error: 1.4094
Epoch 48/300
28/28 [==============================] - 0s 3ms/step - loss: 3.0052 - mean_absolute_error: 1.3600 - val_loss: 2.3798 - val_mean_absolute_error: 1.3735
Epoch 49/300
28/28 [==============================] - 0s 3ms/step - loss: 2.9558 - mean_absolute_error: 1.3610 - val_loss: 2.7502 - val_mean_absolute_error: 1.4935
Epoch 50/300
28/28 [==============================] - 0s 3ms/step - loss: 2.7733 - mean_absolute_error: 1.3102 - val_loss: 2.3574 - val_mean_absolute_error: 1.3670
Epoch 51/300
28/28 [==============================] - 0s 3ms/step - loss: 2.8034 - mean_absolute_error: 1.3184 - val_loss: 2.2890 - val_mean_absolute_error: 1.3441
Epoch 52/300
28/28 [==============================] - 0s 4ms/step - loss: 2.9279 - mean_absolute_error: 1.3533 - val_loss: 2.5444 - val_mean_absolute_error: 1.4292
Epoch 53/300
28/28 [==============================] - 0s 4ms/step - loss: 2.8434 - mean_absolute_error: 1.3326 - val_loss: 2.3529 - val_mean_absolute_error: 1.3659
Epoch 54/300
28/28 [==============================] - 0s 4ms/step - loss: 2.7739 - mean_absolute_error: 1.3074 - val_loss: 2.4340 - val_mean_absolute_error: 1.3932
Epoch 55/300
28/28 [==============================] - 0s 4ms/step - loss: 2.6721 - mean_absolute_error: 1.3009 - val_loss: 2.2762 - val_mean_absolute_error: 1.3404
Epoch 56/300
28/28 [==============================] - 0s 4ms/step - loss: 2.8108 - mean_absolute_error: 1.3255 - val_loss: 2.1926 - val_mean_absolute_error: 1.3118
Epoch 57/300
28/28 [==============================] - 0s 3ms/step - loss: 2.6750 - mean_absolute_error: 1.2815 - val_loss: 2.0743 - val_mean_absolute_error: 1.2702
Epoch 58/300
28/28 [==============================] - 0s 3ms/step - loss: 2.7366 - mean_absolute_error: 1.3001 - val_loss: 2.1798 - val_mean_absolute_error: 1.3078
Epoch 59/300
28/28 [==============================] - 0s 3ms/step - loss: 2.5932 - mean_absolute_error: 1.2573 - val_loss: 2.1022 - val_mean_absolute_error: 1.2799
Epoch 60/300
28/28 [==============================] - 0s 3ms/step - loss: 2.5909 - mean_absolute_error: 1.2723 - val_loss: 2.1165 - val_mean_absolute_error: 1.2858
Epoch 61/300
28/28 [==============================] - 0s 5ms/step - loss: 2.3534 - mean_absolute_error: 1.2164 - val_loss: 2.2087 - val_mean_absolute_error: 1.3183
Epoch 62/300
28/28 [==============================] - 0s 3ms/step - loss: 2.4987 - mean_absolute_error: 1.2453 - val_loss: 1.8638 - val_mean_absolute_error: 1.1928
Epoch 63/300
28/28 [==============================] - 0s 4ms/step - loss: 2.5152 - mean_absolute_error: 1.2527 - val_loss: 1.9940 - val_mean_absolute_error: 1.2415
Epoch 64/300
28/28 [==============================] - 0s 4ms/step - loss: 2.5781 - mean_absolute_error: 1.2666 - val_loss: 2.1161 - val_mean_absolute_error: 1.2858
Epoch 65/300
28/28 [==============================] - 0s 6ms/step - loss: 2.3673 - mean_absolute_error: 1.2139 - val_loss: 1.8202 - val_mean_absolute_error: 1.1765
Epoch 66/300
28/28 [==============================] - 0s 3ms/step - loss: 2.3459 - mean_absolute_error: 1.2105 - val_loss: 1.8923 - val_mean_absolute_error: 1.2040
Epoch 67/300
28/28 [==============================] - 0s 3ms/step - loss: 2.3759 - mean_absolute_error: 1.2186 - val_loss: 2.0204 - val_mean_absolute_error: 1.2509
Epoch 68/300
28/28 [==============================] - 0s 3ms/step - loss: 2.3687 - mean_absolute_error: 1.2152 - val_loss: 2.0155 - val_mean_absolute_error: 1.2493
Epoch 69/300
28/28 [==============================] - 0s 3ms/step - loss: 2.3723 - mean_absolute_error: 1.2073 - val_loss: 1.9139 - val_mean_absolute_error: 1.2122
Epoch 70/300
28/28 [==============================] - 0s 5ms/step - loss: 2.3429 - mean_absolute_error: 1.2011 - val_loss: 1.8465 - val_mean_absolute_error: 1.1869
Epoch 71/300
28/28 [==============================] - 0s 3ms/step - loss: 2.3735 - mean_absolute_error: 1.2152 - val_loss: 1.8780 - val_mean_absolute_error: 1.1987
Epoch 72/300
28/28 [==============================] - 0s 3ms/step - loss: 2.3389 - mean_absolute_error: 1.2039 - val_loss: 1.9206 - val_mean_absolute_error: 1.2141
Epoch 73/300
28/28 [==============================] - 0s 4ms/step - loss: 2.3058 - mean_absolute_error: 1.1853 - val_loss: 1.6729 - val_mean_absolute_error: 1.1201
Epoch 74/300
28/28 [==============================] - 0s 3ms/step - loss: 2.1844 - mean_absolute_error: 1.1684 - val_loss: 1.7059 - val_mean_absolute_error: 1.1334
Epoch 75/300
28/28 [==============================] - 0s 3ms/step - loss: 2.2348 - mean_absolute_error: 1.1868 - val_loss: 1.8330 - val_mean_absolute_error: 1.1824
Epoch 76/300
28/28 [==============================] - 0s 5ms/step - loss: 2.1421 - mean_absolute_error: 1.1554 - val_loss: 1.6731 - val_mean_absolute_error: 1.1203
Epoch 77/300
28/28 [==============================] - 0s 3ms/step - loss: 2.2555 - mean_absolute_error: 1.1872 - val_loss: 1.5946 - val_mean_absolute_error: 1.0898
Epoch 78/300
28/28 [==============================] - 0s 5ms/step - loss: 2.1774 - mean_absolute_error: 1.1656 - val_loss: 1.9120 - val_mean_absolute_error: 1.2103
Epoch 79/300
28/28 [==============================] - 0s 4ms/step - loss: 2.1994 - mean_absolute_error: 1.1578 - val_loss: 1.5853 - val_mean_absolute_error: 1.0857
Epoch 80/300
28/28 [==============================] - 0s 5ms/step - loss: 2.2366 - mean_absolute_error: 1.1929 - val_loss: 1.6378 - val_mean_absolute_error: 1.1070
Epoch 81/300
28/28 [==============================] - 0s 6ms/step - loss: 2.0962 - mean_absolute_error: 1.1490 - val_loss: 1.6411 - val_mean_absolute_error: 1.1077
Epoch 82/300
28/28 [==============================] - 0s 5ms/step - loss: 2.2474 - mean_absolute_error: 1.1868 - val_loss: 1.4258 - val_mean_absolute_error: 1.0202
Epoch 83/300
28/28 [==============================] - 0s 3ms/step - loss: 2.1140 - mean_absolute_error: 1.1547 - val_loss: 1.4456 - val_mean_absolute_error: 1.0293
Epoch 84/300
28/28 [==============================] - 0s 4ms/step - loss: 2.1612 - mean_absolute_error: 1.1541 - val_loss: 1.4819 - val_mean_absolute_error: 1.0445
Epoch 85/300
28/28 [==============================] - 0s 3ms/step - loss: 2.0371 - mean_absolute_error: 1.1222 - val_loss: 1.3556 - val_mean_absolute_error: 0.9909
Epoch 86/300
28/28 [==============================] - 0s 3ms/step - loss: 2.0053 - mean_absolute_error: 1.1235 - val_loss: 1.3264 - val_mean_absolute_error: 0.9790
Epoch 87/300
28/28 [==============================] - 0s 5ms/step - loss: 2.0368 - mean_absolute_error: 1.1235 - val_loss: 1.3504 - val_mean_absolute_error: 0.9888
Epoch 88/300
28/28 [==============================] - 0s 4ms/step - loss: 1.9929 - mean_absolute_error: 1.1188 - val_loss: 1.3955 - val_mean_absolute_error: 1.0069
Epoch 89/300
28/28 [==============================] - 0s 3ms/step - loss: 2.0923 - mean_absolute_error: 1.1396 - val_loss: 1.2406 - val_mean_absolute_error: 0.9416
Epoch 90/300
28/28 [==============================] - 0s 4ms/step - loss: 2.0649 - mean_absolute_error: 1.1216 - val_loss: 1.2422 - val_mean_absolute_error: 0.9432
Epoch 91/300
28/28 [==============================] - 0s 3ms/step - loss: 1.9566 - mean_absolute_error: 1.1020 - val_loss: 1.2788 - val_mean_absolute_error: 0.9588
Epoch 92/300
28/28 [==============================] - 0s 3ms/step - loss: 2.0017 - mean_absolute_error: 1.1148 - val_loss: 1.4526 - val_mean_absolute_error: 1.0312
Epoch 93/300
28/28 [==============================] - 0s 4ms/step - loss: 1.9864 - mean_absolute_error: 1.0925 - val_loss: 1.3070 - val_mean_absolute_error: 0.9693
Epoch 94/300
28/28 [==============================] - 0s 3ms/step - loss: 1.9663 - mean_absolute_error: 1.1009 - val_loss: 1.1859 - val_mean_absolute_error: 0.9179
Epoch 95/300
28/28 [==============================] - 0s 3ms/step - loss: 1.9054 - mean_absolute_error: 1.0981 - val_loss: 1.3039 - val_mean_absolute_error: 0.9683
Epoch 96/300
28/28 [==============================] - 0s 3ms/step - loss: 1.9848 - mean_absolute_error: 1.1167 - val_loss: 1.2425 - val_mean_absolute_error: 0.9427
Epoch 97/300
28/28 [==============================] - 0s 5ms/step - loss: 1.8577 - mean_absolute_error: 1.0738 - val_loss: 1.1411 - val_mean_absolute_error: 0.8973
Epoch 98/300
28/28 [==============================] - 0s 3ms/step - loss: 1.8782 - mean_absolute_error: 1.0780 - val_loss: 1.1471 - val_mean_absolute_error: 0.9007
Epoch 99/300
28/28 [==============================] - 0s 4ms/step - loss: 1.8975 - mean_absolute_error: 1.0954 - val_loss: 1.1033 - val_mean_absolute_error: 0.8816
Epoch 100/300
28/28 [==============================] - 0s 4ms/step - loss: 1.9376 - mean_absolute_error: 1.0925 - val_loss: 1.2354 - val_mean_absolute_error: 0.9408
Epoch 101/300
28/28 [==============================] - 0s 4ms/step - loss: 1.8973 - mean_absolute_error: 1.0899 - val_loss: 1.1585 - val_mean_absolute_error: 0.9061
Epoch 102/300
28/28 [==============================] - 0s 3ms/step - loss: 1.7968 - mean_absolute_error: 1.0624 - val_loss: 1.0335 - val_mean_absolute_error: 0.8464
Epoch 103/300
28/28 [==============================] - 0s 4ms/step - loss: 1.8891 - mean_absolute_error: 1.0743 - val_loss: 1.0923 - val_mean_absolute_error: 0.8735
Epoch 104/300
28/28 [==============================] - 0s 3ms/step - loss: 1.8908 - mean_absolute_error: 1.0733 - val_loss: 1.2133 - val_mean_absolute_error: 0.9280
Epoch 105/300
28/28 [==============================] - 0s 3ms/step - loss: 1.8295 - mean_absolute_error: 1.0701 - val_loss: 1.0895 - val_mean_absolute_error: 0.8729
Epoch 106/300
28/28 [==============================] - 0s 3ms/step - loss: 1.9197 - mean_absolute_error: 1.0871 - val_loss: 1.1214 - val_mean_absolute_error: 0.8884
Epoch 107/300
28/28 [==============================] - 0s 3ms/step - loss: 1.6907 - mean_absolute_error: 1.0133 - val_loss: 1.0308 - val_mean_absolute_error: 0.8446
Epoch 108/300
28/28 [==============================] - 0s 5ms/step - loss: 1.8241 - mean_absolute_error: 1.0527 - val_loss: 1.0250 - val_mean_absolute_error: 0.8434
Epoch 109/300
28/28 [==============================] - 0s 4ms/step - loss: 1.7436 - mean_absolute_error: 1.0419 - val_loss: 1.0279 - val_mean_absolute_error: 0.8436
Epoch 110/300
28/28 [==============================] - 0s 3ms/step - loss: 1.8053 - mean_absolute_error: 1.0594 - val_loss: 0.9932 - val_mean_absolute_error: 0.8238
Epoch 111/300
28/28 [==============================] - 0s 4ms/step - loss: 1.7805 - mean_absolute_error: 1.0597 - val_loss: 1.0910 - val_mean_absolute_error: 0.8709
Epoch 112/300
28/28 [==============================] - 0s 4ms/step - loss: 1.7802 - mean_absolute_error: 1.0502 - val_loss: 0.9207 - val_mean_absolute_error: 0.7880
Epoch 113/300
28/28 [==============================] - 0s 4ms/step - loss: 1.7988 - mean_absolute_error: 1.0435 - val_loss: 0.9331 - val_mean_absolute_error: 0.7933
Epoch 114/300
28/28 [==============================] - 0s 4ms/step - loss: 1.7421 - mean_absolute_error: 1.0398 - val_loss: 0.9537 - val_mean_absolute_error: 0.8050
Epoch 115/300
28/28 [==============================] - 0s 4ms/step - loss: 1.7870 - mean_absolute_error: 1.0457 - val_loss: 0.9112 - val_mean_absolute_error: 0.7831
Epoch 116/300
28/28 [==============================] - 0s 4ms/step - loss: 1.6973 - mean_absolute_error: 1.0149 - val_loss: 0.9710 - val_mean_absolute_error: 0.8134
Epoch 117/300
28/28 [==============================] - 0s 3ms/step - loss: 1.7539 - mean_absolute_error: 1.0507 - val_loss: 0.9508 - val_mean_absolute_error: 0.8044
Epoch 118/300
28/28 [==============================] - 0s 5ms/step - loss: 1.6580 - mean_absolute_error: 1.0116 - val_loss: 0.9544 - val_mean_absolute_error: 0.8043
Epoch 119/300
28/28 [==============================] - 0s 5ms/step - loss: 1.7629 - mean_absolute_error: 1.0346 - val_loss: 0.9962 - val_mean_absolute_error: 0.8278
Epoch 120/300
28/28 [==============================] - 0s 3ms/step - loss: 1.6275 - mean_absolute_error: 1.0021 - val_loss: 0.9311 - val_mean_absolute_error: 0.7924
Epoch 121/300
28/28 [==============================] - 0s 4ms/step - loss: 1.6698 - mean_absolute_error: 1.0160 - val_loss: 0.9183 - val_mean_absolute_error: 0.7869
Epoch 122/300
28/28 [==============================] - 0s 5ms/step - loss: 1.6478 - mean_absolute_error: 1.0056 - val_loss: 0.9157 - val_mean_absolute_error: 0.7841
Epoch 123/300
28/28 [==============================] - 0s 5ms/step - loss: 1.5834 - mean_absolute_error: 0.9818 - val_loss: 0.8718 - val_mean_absolute_error: 0.7625
Epoch 124/300
28/28 [==============================] - 0s 4ms/step - loss: 1.6264 - mean_absolute_error: 1.0133 - val_loss: 0.9159 - val_mean_absolute_error: 0.7842
Epoch 125/300
28/28 [==============================] - 0s 4ms/step - loss: 1.5312 - mean_absolute_error: 0.9658 - val_loss: 0.9124 - val_mean_absolute_error: 0.7826
Epoch 126/300
28/28 [==============================] - 0s 4ms/step - loss: 1.6173 - mean_absolute_error: 0.9975 - val_loss: 0.9388 - val_mean_absolute_error: 0.7973
Epoch 127/300
28/28 [==============================] - 0s 5ms/step - loss: 1.6392 - mean_absolute_error: 0.9954 - val_loss: 0.7704 - val_mean_absolute_error: 0.7032
Epoch 128/300
28/28 [==============================] - 0s 5ms/step - loss: 1.6872 - mean_absolute_error: 1.0126 - val_loss: 0.9208 - val_mean_absolute_error: 0.7867
Epoch 129/300
28/28 [==============================] - 0s 4ms/step - loss: 1.6080 - mean_absolute_error: 0.9902 - val_loss: 0.8352 - val_mean_absolute_error: 0.7403
Epoch 130/300
28/28 [==============================] - 0s 5ms/step - loss: 1.5642 - mean_absolute_error: 0.9887 - val_loss: 0.7865 - val_mean_absolute_error: 0.7108
Epoch 131/300
28/28 [==============================] - 0s 6ms/step - loss: 1.5486 - mean_absolute_error: 0.9765 - val_loss: 0.8681 - val_mean_absolute_error: 0.7569
Epoch 132/300
28/28 [==============================] - 0s 3ms/step - loss: 1.4686 - mean_absolute_error: 0.9520 - val_loss: 0.8827 - val_mean_absolute_error: 0.7660
Epoch 133/300
28/28 [==============================] - 0s 3ms/step - loss: 1.5053 - mean_absolute_error: 0.9653 - val_loss: 0.8598 - val_mean_absolute_error: 0.7525
Epoch 134/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4959 - mean_absolute_error: 0.9577 - val_loss: 0.9143 - val_mean_absolute_error: 0.7833
Epoch 135/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4768 - mean_absolute_error: 0.9437 - val_loss: 0.8142 - val_mean_absolute_error: 0.7278
Epoch 136/300
28/28 [==============================] - 0s 4ms/step - loss: 1.5567 - mean_absolute_error: 0.9824 - val_loss: 0.8560 - val_mean_absolute_error: 0.7509
Epoch 137/300
28/28 [==============================] - 0s 3ms/step - loss: 1.5125 - mean_absolute_error: 0.9727 - val_loss: 0.8456 - val_mean_absolute_error: 0.7453
Epoch 138/300
28/28 [==============================] - 0s 3ms/step - loss: 1.5589 - mean_absolute_error: 0.9750 - val_loss: 0.7669 - val_mean_absolute_error: 0.6994
Epoch 139/300
28/28 [==============================] - 0s 5ms/step - loss: 1.5449 - mean_absolute_error: 0.9648 - val_loss: 0.7697 - val_mean_absolute_error: 0.7000
Epoch 140/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4383 - mean_absolute_error: 0.9512 - val_loss: 0.7678 - val_mean_absolute_error: 0.6985
Epoch 141/300
28/28 [==============================] - 0s 3ms/step - loss: 1.4353 - mean_absolute_error: 0.9484 - val_loss: 0.8291 - val_mean_absolute_error: 0.7357
Epoch 142/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4377 - mean_absolute_error: 0.9389 - val_loss: 0.7524 - val_mean_absolute_error: 0.6883
Epoch 143/300
28/28 [==============================] - 0s 4ms/step - loss: 1.5361 - mean_absolute_error: 0.9742 - val_loss: 0.7627 - val_mean_absolute_error: 0.6949
Epoch 144/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4673 - mean_absolute_error: 0.9486 - val_loss: 0.8371 - val_mean_absolute_error: 0.7423
Epoch 145/300
28/28 [==============================] - 0s 3ms/step - loss: 1.4424 - mean_absolute_error: 0.9420 - val_loss: 0.7906 - val_mean_absolute_error: 0.7124
Epoch 146/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4411 - mean_absolute_error: 0.9425 - val_loss: 0.8273 - val_mean_absolute_error: 0.7343
Epoch 147/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4221 - mean_absolute_error: 0.9365 - val_loss: 0.7777 - val_mean_absolute_error: 0.7060
Epoch 148/300
28/28 [==============================] - 0s 5ms/step - loss: 1.4619 - mean_absolute_error: 0.9541 - val_loss: 0.7726 - val_mean_absolute_error: 0.6984
Epoch 149/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4534 - mean_absolute_error: 0.9529 - val_loss: 0.7541 - val_mean_absolute_error: 0.6918
Epoch 150/300
28/28 [==============================] - 0s 4ms/step - loss: 1.3674 - mean_absolute_error: 0.9266 - val_loss: 0.7719 - val_mean_absolute_error: 0.7019
Epoch 151/300
28/28 [==============================] - 0s 3ms/step - loss: 1.3634 - mean_absolute_error: 0.9223 - val_loss: 0.8182 - val_mean_absolute_error: 0.7301
Epoch 152/300
28/28 [==============================] - 0s 4ms/step - loss: 1.4122 - mean_absolute_error: 0.9265 - val_loss: 0.7466 - val_mean_absolute_error: 0.6867
Epoch 153/300
28/28 [==============================] - 0s 4ms/step - loss: 1.3896 - mean_absolute_error: 0.9307 - val_loss: 0.7871 - val_mean_absolute_error: 0.7116
Epoch 154/300
28/28 [==============================] - 0s 5ms/step - loss: 1.4599 - mean_absolute_error: 0.9477 - val_loss: 0.7268 - val_mean_absolute_error: 0.6753
Epoch 155/300
28/28 [==============================] - 0s 3ms/step - loss: 1.3867 - mean_absolute_error: 0.9153 - val_loss: 0.9033 - val_mean_absolute_error: 0.7776
Epoch 156/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2890 - mean_absolute_error: 0.8894 - val_loss: 0.7472 - val_mean_absolute_error: 0.6834
Epoch 157/300
28/28 [==============================] - 0s 3ms/step - loss: 1.4504 - mean_absolute_error: 0.9401 - val_loss: 0.7675 - val_mean_absolute_error: 0.7001
Epoch 158/300
28/28 [==============================] - 0s 3ms/step - loss: 1.4331 - mean_absolute_error: 0.9322 - val_loss: 0.7465 - val_mean_absolute_error: 0.6878
Epoch 159/300
28/28 [==============================] - 0s 3ms/step - loss: 1.4015 - mean_absolute_error: 0.9308 - val_loss: 0.7528 - val_mean_absolute_error: 0.6916
Epoch 160/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2886 - mean_absolute_error: 0.8923 - val_loss: 0.7040 - val_mean_absolute_error: 0.6577
Epoch 161/300
28/28 [==============================] - 0s 4ms/step - loss: 1.3168 - mean_absolute_error: 0.9014 - val_loss: 0.7865 - val_mean_absolute_error: 0.7114
Epoch 162/300
28/28 [==============================] - 0s 4ms/step - loss: 1.3968 - mean_absolute_error: 0.9151 - val_loss: 0.8528 - val_mean_absolute_error: 0.7491
Epoch 163/300
28/28 [==============================] - 0s 3ms/step - loss: 1.3205 - mean_absolute_error: 0.9027 - val_loss: 0.7695 - val_mean_absolute_error: 0.6996
Epoch 164/300
28/28 [==============================] - 0s 3ms/step - loss: 1.3335 - mean_absolute_error: 0.9025 - val_loss: 0.7119 - val_mean_absolute_error: 0.6625
Epoch 165/300
28/28 [==============================] - 0s 3ms/step - loss: 1.2857 - mean_absolute_error: 0.8886 - val_loss: 0.8424 - val_mean_absolute_error: 0.7426
Epoch 166/300
28/28 [==============================] - 0s 3ms/step - loss: 1.2927 - mean_absolute_error: 0.8896 - val_loss: 0.7407 - val_mean_absolute_error: 0.6822
Epoch 167/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1975 - mean_absolute_error: 0.8466 - val_loss: 0.7303 - val_mean_absolute_error: 0.6749
Epoch 168/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2794 - mean_absolute_error: 0.8934 - val_loss: 0.7632 - val_mean_absolute_error: 0.6957
Epoch 169/300
28/28 [==============================] - 0s 4ms/step - loss: 1.3016 - mean_absolute_error: 0.8988 - val_loss: 0.7352 - val_mean_absolute_error: 0.6782
Epoch 170/300
28/28 [==============================] - 0s 3ms/step - loss: 1.2603 - mean_absolute_error: 0.8809 - val_loss: 0.7021 - val_mean_absolute_error: 0.6559
Epoch 171/300
28/28 [==============================] - 0s 3ms/step - loss: 1.3196 - mean_absolute_error: 0.8968 - val_loss: 0.7595 - val_mean_absolute_error: 0.6957
Epoch 172/300
28/28 [==============================] - 0s 3ms/step - loss: 1.2428 - mean_absolute_error: 0.8778 - val_loss: 0.7862 - val_mean_absolute_error: 0.7102
Epoch 173/300
28/28 [==============================] - 0s 3ms/step - loss: 1.2939 - mean_absolute_error: 0.8984 - val_loss: 0.6970 - val_mean_absolute_error: 0.6526
Epoch 174/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2271 - mean_absolute_error: 0.8660 - val_loss: 0.7867 - val_mean_absolute_error: 0.7110
Epoch 175/300
28/28 [==============================] - 0s 5ms/step - loss: 1.3029 - mean_absolute_error: 0.8910 - val_loss: 0.7106 - val_mean_absolute_error: 0.6613
Epoch 176/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2397 - mean_absolute_error: 0.8653 - val_loss: 0.7802 - val_mean_absolute_error: 0.7040
Epoch 177/300
28/28 [==============================] - 0s 3ms/step - loss: 1.2355 - mean_absolute_error: 0.8586 - val_loss: 0.7250 - val_mean_absolute_error: 0.6706
Epoch 178/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1870 - mean_absolute_error: 0.8542 - val_loss: 0.7032 - val_mean_absolute_error: 0.6550
Epoch 179/300
28/28 [==============================] - 0s 6ms/step - loss: 1.1804 - mean_absolute_error: 0.8485 - val_loss: 0.7493 - val_mean_absolute_error: 0.6828
Epoch 180/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1813 - mean_absolute_error: 0.8564 - val_loss: 0.7243 - val_mean_absolute_error: 0.6689
Epoch 181/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1689 - mean_absolute_error: 0.8501 - val_loss: 0.6663 - val_mean_absolute_error: 0.6265
Epoch 182/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2228 - mean_absolute_error: 0.8629 - val_loss: 0.7409 - val_mean_absolute_error: 0.6800
Epoch 183/300
28/28 [==============================] - 0s 4ms/step - loss: 1.1834 - mean_absolute_error: 0.8436 - val_loss: 0.7644 - val_mean_absolute_error: 0.6939
Epoch 184/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1810 - mean_absolute_error: 0.8518 - val_loss: 0.7298 - val_mean_absolute_error: 0.6703
Epoch 185/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2651 - mean_absolute_error: 0.8849 - val_loss: 0.6977 - val_mean_absolute_error: 0.6518
Epoch 186/300
28/28 [==============================] - 0s 4ms/step - loss: 1.1825 - mean_absolute_error: 0.8483 - val_loss: 0.7552 - val_mean_absolute_error: 0.6882
Epoch 187/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1582 - mean_absolute_error: 0.8361 - val_loss: 0.7408 - val_mean_absolute_error: 0.6795
Epoch 188/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2393 - mean_absolute_error: 0.8719 - val_loss: 0.7454 - val_mean_absolute_error: 0.6813
Epoch 189/300
28/28 [==============================] - 0s 4ms/step - loss: 1.1232 - mean_absolute_error: 0.8394 - val_loss: 0.6989 - val_mean_absolute_error: 0.6525
Epoch 190/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1432 - mean_absolute_error: 0.8357 - val_loss: 0.7759 - val_mean_absolute_error: 0.7014
Epoch 191/300
28/28 [==============================] - 0s 4ms/step - loss: 1.2190 - mean_absolute_error: 0.8689 - val_loss: 0.7247 - val_mean_absolute_error: 0.6707
Epoch 192/300
28/28 [==============================] - 0s 5ms/step - loss: 1.1771 - mean_absolute_error: 0.8546 - val_loss: 0.6644 - val_mean_absolute_error: 0.6288
Epoch 193/300
28/28 [==============================] - 0s 5ms/step - loss: 1.2142 - mean_absolute_error: 0.8612 - val_loss: 0.8063 - val_mean_absolute_error: 0.7215
Epoch 194/300
28/28 [==============================] - 0s 4ms/step - loss: 1.1358 - mean_absolute_error: 0.8337 - val_loss: 0.6985 - val_mean_absolute_error: 0.6509
Epoch 195/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1092 - mean_absolute_error: 0.8259 - val_loss: 0.7228 - val_mean_absolute_error: 0.6701
Epoch 196/300
28/28 [==============================] - 0s 5ms/step - loss: 1.1428 - mean_absolute_error: 0.8354 - val_loss: 0.6876 - val_mean_absolute_error: 0.6449
Epoch 197/300
28/28 [==============================] - 0s 4ms/step - loss: 1.1550 - mean_absolute_error: 0.8408 - val_loss: 0.6989 - val_mean_absolute_error: 0.6511
Epoch 198/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0729 - mean_absolute_error: 0.8172 - val_loss: 0.6756 - val_mean_absolute_error: 0.6367
Epoch 199/300
28/28 [==============================] - 0s 4ms/step - loss: 1.1402 - mean_absolute_error: 0.8345 - val_loss: 0.7690 - val_mean_absolute_error: 0.6979
Epoch 200/300
28/28 [==============================] - 0s 4ms/step - loss: 1.1535 - mean_absolute_error: 0.8392 - val_loss: 0.7033 - val_mean_absolute_error: 0.6528
Epoch 201/300
28/28 [==============================] - 0s 3ms/step - loss: 1.1610 - mean_absolute_error: 0.8413 - val_loss: 0.7099 - val_mean_absolute_error: 0.6599
Epoch 202/300
28/28 [==============================] - 0s 4ms/step - loss: 1.0172 - mean_absolute_error: 0.7962 - val_loss: 0.7019 - val_mean_absolute_error: 0.6531
Epoch 203/300
28/28 [==============================] - 0s 5ms/step - loss: 1.0657 - mean_absolute_error: 0.8148 - val_loss: 0.7071 - val_mean_absolute_error: 0.6581
Epoch 204/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0916 - mean_absolute_error: 0.8159 - val_loss: 0.6844 - val_mean_absolute_error: 0.6418
Epoch 205/300
28/28 [==============================] - 0s 4ms/step - loss: 1.0403 - mean_absolute_error: 0.7941 - val_loss: 0.6646 - val_mean_absolute_error: 0.6291
Epoch 206/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0362 - mean_absolute_error: 0.8030 - val_loss: 0.7114 - val_mean_absolute_error: 0.6612
Epoch 207/300
28/28 [==============================] - 0s 5ms/step - loss: 1.0712 - mean_absolute_error: 0.8000 - val_loss: 0.6571 - val_mean_absolute_error: 0.6214
Epoch 208/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0416 - mean_absolute_error: 0.7964 - val_loss: 0.6958 - val_mean_absolute_error: 0.6503
Epoch 209/300
28/28 [==============================] - 0s 4ms/step - loss: 1.0071 - mean_absolute_error: 0.7774 - val_loss: 0.7255 - val_mean_absolute_error: 0.6708
Epoch 210/300
28/28 [==============================] - 0s 4ms/step - loss: 1.0407 - mean_absolute_error: 0.7997 - val_loss: 0.6796 - val_mean_absolute_error: 0.6397
Epoch 211/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0676 - mean_absolute_error: 0.8044 - val_loss: 0.6939 - val_mean_absolute_error: 0.6460
Epoch 212/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0680 - mean_absolute_error: 0.8037 - val_loss: 0.6518 - val_mean_absolute_error: 0.6159
Epoch 213/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0279 - mean_absolute_error: 0.8009 - val_loss: 0.7223 - val_mean_absolute_error: 0.6660
Epoch 214/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0692 - mean_absolute_error: 0.8180 - val_loss: 0.6826 - val_mean_absolute_error: 0.6398
Epoch 215/300
28/28 [==============================] - 0s 5ms/step - loss: 1.0268 - mean_absolute_error: 0.7934 - val_loss: 0.6585 - val_mean_absolute_error: 0.6246
Epoch 216/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0644 - mean_absolute_error: 0.8115 - val_loss: 0.6826 - val_mean_absolute_error: 0.6376
Epoch 217/300
28/28 [==============================] - 0s 4ms/step - loss: 1.0072 - mean_absolute_error: 0.7850 - val_loss: 0.6964 - val_mean_absolute_error: 0.6506
Epoch 218/300
28/28 [==============================] - 0s 4ms/step - loss: 1.0091 - mean_absolute_error: 0.7763 - val_loss: 0.7019 - val_mean_absolute_error: 0.6537
Epoch 219/300
28/28 [==============================] - 0s 5ms/step - loss: 1.0125 - mean_absolute_error: 0.7824 - val_loss: 0.7193 - val_mean_absolute_error: 0.6642
Epoch 220/300
28/28 [==============================] - 0s 5ms/step - loss: 0.9496 - mean_absolute_error: 0.7638 - val_loss: 0.6751 - val_mean_absolute_error: 0.6342
Epoch 221/300
28/28 [==============================] - 0s 4ms/step - loss: 1.0178 - mean_absolute_error: 0.7821 - val_loss: 0.7394 - val_mean_absolute_error: 0.6784
Epoch 222/300
28/28 [==============================] - 0s 6ms/step - loss: 0.9663 - mean_absolute_error: 0.7737 - val_loss: 0.6935 - val_mean_absolute_error: 0.6464
Epoch 223/300
28/28 [==============================] - 0s 3ms/step - loss: 0.9723 - mean_absolute_error: 0.7661 - val_loss: 0.7098 - val_mean_absolute_error: 0.6591
Epoch 224/300
28/28 [==============================] - 0s 3ms/step - loss: 0.9531 - mean_absolute_error: 0.7670 - val_loss: 0.7240 - val_mean_absolute_error: 0.6678
Epoch 225/300
28/28 [==============================] - 0s 3ms/step - loss: 1.0046 - mean_absolute_error: 0.7880 - val_loss: 0.6686 - val_mean_absolute_error: 0.6320
Epoch 226/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9328 - mean_absolute_error: 0.7557 - val_loss: 0.6685 - val_mean_absolute_error: 0.6310
Epoch 227/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9400 - mean_absolute_error: 0.7504 - val_loss: 0.6683 - val_mean_absolute_error: 0.6332
Epoch 228/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9334 - mean_absolute_error: 0.7543 - val_loss: 0.6971 - val_mean_absolute_error: 0.6518
Epoch 229/300
28/28 [==============================] - 0s 3ms/step - loss: 0.9673 - mean_absolute_error: 0.7683 - val_loss: 0.6755 - val_mean_absolute_error: 0.6360
Epoch 230/300
28/28 [==============================] - 0s 5ms/step - loss: 0.9584 - mean_absolute_error: 0.7588 - val_loss: 0.7256 - val_mean_absolute_error: 0.6675
Epoch 231/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9449 - mean_absolute_error: 0.7527 - val_loss: 0.6344 - val_mean_absolute_error: 0.6097
Epoch 232/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9690 - mean_absolute_error: 0.7638 - val_loss: 0.7042 - val_mean_absolute_error: 0.6545
Epoch 233/300
28/28 [==============================] - 0s 3ms/step - loss: 0.9308 - mean_absolute_error: 0.7531 - val_loss: 0.6879 - val_mean_absolute_error: 0.6434
Epoch 234/300
28/28 [==============================] - 0s 3ms/step - loss: 0.9155 - mean_absolute_error: 0.7396 - val_loss: 0.6629 - val_mean_absolute_error: 0.6280
Epoch 235/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8972 - mean_absolute_error: 0.7373 - val_loss: 0.7066 - val_mean_absolute_error: 0.6597
Epoch 236/300
28/28 [==============================] - 0s 5ms/step - loss: 0.9193 - mean_absolute_error: 0.7494 - val_loss: 0.6877 - val_mean_absolute_error: 0.6450
Epoch 237/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8887 - mean_absolute_error: 0.7399 - val_loss: 0.6928 - val_mean_absolute_error: 0.6481
Epoch 238/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9263 - mean_absolute_error: 0.7498 - val_loss: 0.6943 - val_mean_absolute_error: 0.6501
Epoch 239/300
28/28 [==============================] - 0s 5ms/step - loss: 0.9355 - mean_absolute_error: 0.7598 - val_loss: 0.7055 - val_mean_absolute_error: 0.6575
Epoch 240/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9225 - mean_absolute_error: 0.7513 - val_loss: 0.6962 - val_mean_absolute_error: 0.6514
Epoch 241/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8890 - mean_absolute_error: 0.7418 - val_loss: 0.7349 - val_mean_absolute_error: 0.6765
Epoch 242/300
28/28 [==============================] - 0s 5ms/step - loss: 0.8696 - mean_absolute_error: 0.7293 - val_loss: 0.7158 - val_mean_absolute_error: 0.6635
Epoch 243/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9299 - mean_absolute_error: 0.7552 - val_loss: 0.6875 - val_mean_absolute_error: 0.6447
Epoch 244/300
28/28 [==============================] - 0s 5ms/step - loss: 0.8664 - mean_absolute_error: 0.7147 - val_loss: 0.6753 - val_mean_absolute_error: 0.6374
Epoch 245/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9292 - mean_absolute_error: 0.7466 - val_loss: 0.6672 - val_mean_absolute_error: 0.6325
Epoch 246/300
28/28 [==============================] - 0s 5ms/step - loss: 0.8874 - mean_absolute_error: 0.7414 - val_loss: 0.7166 - val_mean_absolute_error: 0.6633
Epoch 247/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8749 - mean_absolute_error: 0.7382 - val_loss: 0.6624 - val_mean_absolute_error: 0.6239
Epoch 248/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8599 - mean_absolute_error: 0.7284 - val_loss: 0.6962 - val_mean_absolute_error: 0.6513
Epoch 249/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8527 - mean_absolute_error: 0.7205 - val_loss: 0.6846 - val_mean_absolute_error: 0.6443
Epoch 250/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8799 - mean_absolute_error: 0.7372 - val_loss: 0.6859 - val_mean_absolute_error: 0.6428
Epoch 251/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8898 - mean_absolute_error: 0.7339 - val_loss: 0.6761 - val_mean_absolute_error: 0.6370
Epoch 252/300
28/28 [==============================] - 0s 5ms/step - loss: 0.8483 - mean_absolute_error: 0.7233 - val_loss: 0.6826 - val_mean_absolute_error: 0.6419
Epoch 253/300
28/28 [==============================] - 0s 4ms/step - loss: 0.9004 - mean_absolute_error: 0.7335 - val_loss: 0.7016 - val_mean_absolute_error: 0.6542
Epoch 254/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8604 - mean_absolute_error: 0.7272 - val_loss: 0.7045 - val_mean_absolute_error: 0.6552
Epoch 255/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8346 - mean_absolute_error: 0.7190 - val_loss: 0.6753 - val_mean_absolute_error: 0.6367
Epoch 256/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8708 - mean_absolute_error: 0.7244 - val_loss: 0.7074 - val_mean_absolute_error: 0.6563
Epoch 257/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8124 - mean_absolute_error: 0.7056 - val_loss: 0.6695 - val_mean_absolute_error: 0.6317
Epoch 258/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8635 - mean_absolute_error: 0.7247 - val_loss: 0.7265 - val_mean_absolute_error: 0.6702
Epoch 259/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8657 - mean_absolute_error: 0.7210 - val_loss: 0.6513 - val_mean_absolute_error: 0.6207
Epoch 260/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8363 - mean_absolute_error: 0.7073 - val_loss: 0.6872 - val_mean_absolute_error: 0.6442
Epoch 261/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8477 - mean_absolute_error: 0.7237 - val_loss: 0.6947 - val_mean_absolute_error: 0.6490
Epoch 262/300
28/28 [==============================] - 0s 5ms/step - loss: 0.8247 - mean_absolute_error: 0.7013 - val_loss: 0.6766 - val_mean_absolute_error: 0.6381
Epoch 263/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7800 - mean_absolute_error: 0.6922 - val_loss: 0.6606 - val_mean_absolute_error: 0.6265
Epoch 264/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8393 - mean_absolute_error: 0.7065 - val_loss: 0.6827 - val_mean_absolute_error: 0.6417
Epoch 265/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7798 - mean_absolute_error: 0.6970 - val_loss: 0.7109 - val_mean_absolute_error: 0.6617
Epoch 266/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7798 - mean_absolute_error: 0.6892 - val_loss: 0.6661 - val_mean_absolute_error: 0.6299
Epoch 267/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8127 - mean_absolute_error: 0.6982 - val_loss: 0.6852 - val_mean_absolute_error: 0.6428
Epoch 268/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8212 - mean_absolute_error: 0.7150 - val_loss: 0.6502 - val_mean_absolute_error: 0.6192
Epoch 269/300
28/28 [==============================] - 0s 5ms/step - loss: 0.8054 - mean_absolute_error: 0.6943 - val_loss: 0.7302 - val_mean_absolute_error: 0.6731
Epoch 270/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8051 - mean_absolute_error: 0.6991 - val_loss: 0.6650 - val_mean_absolute_error: 0.6306
Epoch 271/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8009 - mean_absolute_error: 0.6950 - val_loss: 0.7107 - val_mean_absolute_error: 0.6605
Epoch 272/300
28/28 [==============================] - 1s 24ms/step - loss: 0.7630 - mean_absolute_error: 0.6861 - val_loss: 0.6430 - val_mean_absolute_error: 0.6150
Epoch 273/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7961 - mean_absolute_error: 0.6994 - val_loss: 0.6803 - val_mean_absolute_error: 0.6395
Epoch 274/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7747 - mean_absolute_error: 0.6865 - val_loss: 0.6887 - val_mean_absolute_error: 0.6443
Epoch 275/300
28/28 [==============================] - 0s 3ms/step - loss: 0.8108 - mean_absolute_error: 0.6957 - val_loss: 0.7091 - val_mean_absolute_error: 0.6593
Epoch 276/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8030 - mean_absolute_error: 0.6921 - val_loss: 0.6436 - val_mean_absolute_error: 0.6127
Epoch 277/300
28/28 [==============================] - 0s 5ms/step - loss: 0.7670 - mean_absolute_error: 0.6841 - val_loss: 0.6945 - val_mean_absolute_error: 0.6512
Epoch 278/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7909 - mean_absolute_error: 0.6870 - val_loss: 0.6568 - val_mean_absolute_error: 0.6235
Epoch 279/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7715 - mean_absolute_error: 0.6825 - val_loss: 0.6879 - val_mean_absolute_error: 0.6458
Epoch 280/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7948 - mean_absolute_error: 0.6954 - val_loss: 0.6419 - val_mean_absolute_error: 0.6126
Epoch 281/300
28/28 [==============================] - 0s 4ms/step - loss: 0.8060 - mean_absolute_error: 0.6941 - val_loss: 0.6524 - val_mean_absolute_error: 0.6201
Epoch 282/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7549 - mean_absolute_error: 0.6739 - val_loss: 0.6887 - val_mean_absolute_error: 0.6463
Epoch 283/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7642 - mean_absolute_error: 0.6760 - val_loss: 0.6451 - val_mean_absolute_error: 0.6162
Epoch 284/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7741 - mean_absolute_error: 0.6843 - val_loss: 0.7004 - val_mean_absolute_error: 0.6535
Epoch 285/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7669 - mean_absolute_error: 0.6851 - val_loss: 0.7046 - val_mean_absolute_error: 0.6560
Epoch 286/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7271 - mean_absolute_error: 0.6720 - val_loss: 0.6705 - val_mean_absolute_error: 0.6335
Epoch 287/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7578 - mean_absolute_error: 0.6688 - val_loss: 0.6869 - val_mean_absolute_error: 0.6426
Epoch 288/300
28/28 [==============================] - 0s 5ms/step - loss: 0.7916 - mean_absolute_error: 0.6813 - val_loss: 0.6607 - val_mean_absolute_error: 0.6260
Epoch 289/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7595 - mean_absolute_error: 0.6766 - val_loss: 0.6544 - val_mean_absolute_error: 0.6217
Epoch 290/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7942 - mean_absolute_error: 0.6933 - val_loss: 0.6652 - val_mean_absolute_error: 0.6295
Epoch 291/300
28/28 [==============================] - 0s 5ms/step - loss: 0.7110 - mean_absolute_error: 0.6589 - val_loss: 0.6871 - val_mean_absolute_error: 0.6450
Epoch 292/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7282 - mean_absolute_error: 0.6684 - val_loss: 0.6494 - val_mean_absolute_error: 0.6184
Epoch 293/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7787 - mean_absolute_error: 0.6863 - val_loss: 0.6561 - val_mean_absolute_error: 0.6225
Epoch 294/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7434 - mean_absolute_error: 0.6720 - val_loss: 0.6879 - val_mean_absolute_error: 0.6446
Epoch 295/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7588 - mean_absolute_error: 0.6760 - val_loss: 0.6504 - val_mean_absolute_error: 0.6158
Epoch 296/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7149 - mean_absolute_error: 0.6537 - val_loss: 0.6286 - val_mean_absolute_error: 0.6006
Epoch 297/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7411 - mean_absolute_error: 0.6674 - val_loss: 0.6759 - val_mean_absolute_error: 0.6369
Epoch 298/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7597 - mean_absolute_error: 0.6734 - val_loss: 0.6674 - val_mean_absolute_error: 0.6296
Epoch 299/300
28/28 [==============================] - 0s 3ms/step - loss: 0.7636 - mean_absolute_error: 0.6800 - val_loss: 0.6623 - val_mean_absolute_error: 0.6270
Epoch 300/300
28/28 [==============================] - 0s 4ms/step - loss: 0.7579 - mean_absolute_error: 0.6799 - val_loss: 0.6679 - val_mean_absolute_error: 0.6314
The r2 score is: 0.26
The mean absolut error score is: 0.65
The mean squared error score is: 0.83
plot_NN_losses(history)
Jan = final_movie_dataset.copy()
Jan = Jan_mod1(Jan)
Seasons
Jan = create_season(Jan)
movies_genre_season(Jan)
movie_keyfigures_by_season(Jan)
genre_pie(Jan)
genre_season(Jan)
christmas_movies(Jan)
title genre score
1426 The Shawshank Redemption Drama 9.3
1427 Pulp Fiction Crime 8.9
2771 The Lord of the Rings: The Return of the King Action 8.9
1294 Schindler's List Biography 8.9
2450 The Lord of the Rings: The Fellowship of the Ring Action 8.8
Dump season
plot_number_score_dumpseason(Jan)
zoom_plot_ds(Jan)
gross_budget_good_bad(Jan)
good_bad_norm(Jan)
histograms_dumpmonths(Jan)