Question

所以我成功地将我的数据集拆分为Train＆amp;以70:30的比例进行测试我用过这个：

df_glass['split'] = np.random.randn(df_glass.shape[0], 1)
msk = np.random.rand(len(df_glass)) <= 0.7
train = df_glass[msk]
test = df_glass[~msk]
print(train)
print(test)

现在，如何将训练和测试分成X_train和y_train以及X_test和y_test 这样，X表示数据库的特征，y表示响应？

我需要进行有监督的学习，并在X_Train和y_Train上应用ML模块。

我的数据库如下所示： Database_snippet

Answer 1

Scikit-Learn有一种方便的方法来分割pandas数据帧 -

这将进行拆分 -

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(df[list_of_X_cols], df['y'], test_size=0.33, random_state=42)

Answer 2

我猜你可能会发现这对理解很有用..

import pandas as pd
from sklearn.cross_validation import train_test_split
from sklearn.linear_model import LinearRegression

#importing dataset
dataset = pd.read_csv('Salary_Data.csv')
x = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 1].values

#spliting the dataset into training and test set
x_train, x_test, y_train, y_test = train_test_split(x, y, 
test_size=1/3, random_state=0)

如何将训练和测试数据集拆分为X_Train y_train和X_Test y_Test？

2 个答案: