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목록Feature Engineering (1)
Deeper Learning
Feature Engineering
import numpy as np import pandas as pd from sklearn.datasets import fetch_california_housing x,y = fetch_california_housing(return_X_y=True) k=fetch_california_housing() k.feature_names print(x.shape) print(y.shape) np.random.seed(1127) shuffle_ind = np.random.permutation(x.shape[0]) x=x[shuffle_ind,:] y=y[shuffle_ind] x_train = x[:int(x.shape[0]*0.8),:] y_train = y[:int(x.shape[0]*0.8)] x_test ..
AI/Machine Learning & Data Science
2020. 11. 27. 22:56