Class IterativeReliefOnline

FeaturewiseDatasetMeasure that performs multivariate I-RELIEF algorithm. Online version.

This algorithm is exactly the one in the referenced paper (I-RELIEF-2 online), using weighted 1-norm and Exponential Kernel.

Nested Classes

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods

__init__(self, a=10.0, permute=True, max_iter=3, **kwargs)
Constructor of the IRELIEF class.

source code

_call(self, dataset)
Computes featurewise I-RELIEF-2 weights. Online version.

source code

Inherited from IterativeRelief: compute_M_H, k

Inherited from base.FeaturewiseDatasetMeasure: __repr__, combiner

Inherited from base.FeaturewiseDatasetMeasure (private): _postcall

Inherited from base.DatasetMeasure: __call__, null_dist, transformer, untrain

Inherited from misc.state.ClassWithCollections: __getattribute__, __new__, __setattr__, __str__, reset

Inherited from object: __delattr__, __format__, __hash__, __reduce__, __reduce_ex__, __sizeof__, __subclasshook__

Class Variables

Inherited from base.FeaturewiseDatasetMeasure: base_sensitivities

Inherited from base.DatasetMeasure: __doc__, null_prob, null_t, raw_results

Inherited from misc.state.ClassWithCollections: _DEV__doc__, descr

Properties

Inherited from object: __class__

Method Details

Constructor of the IRELIEF class.

Parameters:

combiner - The combiner is only applied if the computed featurewise dataset measure is more than one-dimensional. This is different from a transformer, which is always applied. By default, the sum of absolute values along the second axis is computed.

Overrides: object.__init__

Computes featurewise I-RELIEF-2 weights. Online version.

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