mlens.base.id_train module¶
ML-ENSEMBLE
author: | Sebastian Flennerhag |
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copyright: | 2017 |
licence: | MIT |
Class for identifying a training set after an estimator has been fitted. Used for determining whether a predict or transform method should use cross validation to create predictions, or estimators fitted on full training data.
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class
mlens.base.id_train.
IdTrain
(size=10)[source]¶ Bases:
mlens.externals.sklearn.base.BaseEstimator
Container to identify training set.
Samples a random subset from set passed to the fit method, to allow identification of the training set in a transform or predict method.
Parameters: size (int) – size to sample. A random subset of size [size, size] will be stored in the instance.
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mlens.base.id_train.
permutation
(x)¶ Randomly permute a sequence, or return a permuted range.
If x is a multi-dimensional array, it is only shuffled along its first index.
Parameters: x (int or array_like) – If x is an integer, randomly permute np.arange(x)
. If x is an array, make a copy and shuffle the elements randomly.Returns: out – Permuted sequence or array range. Return type: ndarray Examples
>>> np.random.permutation(10) array([1, 7, 4, 3, 0, 9, 2, 5, 8, 6])
>>> np.random.permutation([1, 4, 9, 12, 15]) array([15, 1, 9, 4, 12])
>>> arr = np.arange(9).reshape((3, 3)) >>> np.random.permutation(arr) array([[6, 7, 8], [0, 1, 2], [3, 4, 5]])