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sklearn.model_selection

sklearn.model_selection.train_test_split

sklearn.model_selection.train_test_split(X, y, test_size=None, train_size=None, random_state=None, shuffle=True, stratify=None)


Supported Arguments

  • X: NumPy array or Pandas Dataframes.
  • y: NumPy array or Pandas Dataframes.
  • train_size: float between 0.0 and 1.0 or None only.
  • test_size: float between 0.0 and 1.0 or None only.
  • random_state: int, RandomState, or None.
  • shuffle: bool.

Example Usage

>>> import bodo
>>> import numpy as np
>>> from sklearn.model_selection import train_test_split
>>> @bodo.jit
>>> def test_split():
...   X, y = np.arange(10).reshape(5, 2), np.arange(5)
...   X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.33, random_state=42)
...   print(X_train)
...   print(y_train)
X_train:  [[4 5]
[6 7]
[8 9]]
y_train:  [2 3 4]
X_test:  [[2 3]
[0 1]]
y_test:  [1 0]
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