Cross Validation¶
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pykitml.
cross_validate
(inputs, outputs, folds=5)¶ Python generator function for making K-fold cross validation easier.
Parameters: - inputs (numpy.array) – Inputs/features of training data.
- outputs (numpy.array) – Outputs/targets of training data.
Yields: - train_inputs (numpy.array) – Training data containing inputs.
- train_outputs (numpy.array) – Training data containing outputs.
- test_inputs (numpy.array) – Testing data containing inputs.
- test_outputs (numpy.array) – Testing data containing outputs.
Example
>>> import numpy as np >>> import pykitml as pk >>> >>> # Mock training data ... x = np.arange(30).reshape((10, 3)) >>> y = x + 10 >>> >>> # 5-fold cross validation ... # Training data is split into 5 blocks, each block takes its turn ... # to be the test data. ... for train_x, train_y, test_x, test_y in pk.cross_validate(x, y, 5): ... print(train_x) ... print(train_y) ... print(test_x) ... print(test_y)