機器學習_ML_train_test_split

切割數據集，做訓練與驗證使用!

IMPORT

from sklearn.model_selection import train_test_split

範例

x:特徵資料集
y:目標資料集
test_size=0.3:代表切了3成去做測試數據集!
random_state:亂數種子，每次設置一樣所得亂數相同!

import pandas as pd
df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data', header=None, sep='\s+')

df.columns = ['CRIM', 'ZN', 'INDUS', 'CHAS', 
              'NOX', 'RM', 'AGE', 'DIS', 'RAD', 
              'TAX', 'PTRATIO', 'B', 'LSTAT', 'MEDV']
#  驗證一下資料有沒有進來
df.head()

x = df[['RM']].values
y = df['MEDV'].values

X_train, X_test, y_train, y_test = train_test_split(X, 
                                                    y, 
                                                    test_size=0.3, 
                                                    random_state=0)