import timeit import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn import datasets,linear_model X,y = datasets.load_diabetes(return_X_y=True) X raw=X[:,None,2]

max_raw=max(raw) min_raw=min(raw) scaled=(2*raw - max_raw - min_raw)/(max_raw-min_raw)

fig, axs = plt.subplots(2,1,sharex= True) axs[0].hist(raw) axs[1].hist(scaled)

# Modelos para entrenamiento def train_raw(): linear_model.Linear