Given 2 datasets, training and testing, I want to divide training dataset into xtrain and ytrain and testing into xtest and ytest. I have the code for octave
X_tr = D_tr(:, 1:end-1);
y_tr = D_tr(:, end);
X_ts = D_ts(:, 1:end-1);
y_ts = D_ts(:, end);
but not able to understand how to convert that into python
Use sklearn.model_selection.train_test_split :
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = \
train_test_split(X, y, test_size=0.33, random_state=42)
Demo: how to split data sets (horizontally) using np.split
:
In [68]: TR = np.random.randint(10, size=(5,5))
In [69]: TR
Out[69]:
array([[2, 9, 9, 0, 3],
[5, 5, 6, 0, 3],
[7, 1, 6, 1, 0],
[5, 0, 2, 0, 4],
[2, 5, 9, 4, 2]])
In [70]: X_tr, y_tr = np.split(TR, [-1], axis=1)
In [71]: X_tr
Out[71]:
array([[2, 9, 9, 0],
[5, 5, 6, 0],
[7, 1, 6, 1],
[5, 0, 2, 0],
[2, 5, 9, 4]])
In [72]: y_tr
Out[72]:
array([[3],
[3],
[0],
[4],
[2]])
PS the same technique would be used for splitting a test data set
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