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PyMVPA: Python MultiVariate Pattern Analysis
Package mvpa :: Package measures :: Module irelief :: Class IterativeRelief_Devel
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Class IterativeRelief_Devel

source code

FeaturewiseDatasetMeasure that performs multivariate I-RELIEF algorithm. Batch version allowing various kernels.

UNDER DEVELOPEMNT.

Batch I-RELIEF-2 feature weighting algorithm. Works for binary or multiclass class-labels. Batch version with complexity O(T*N^2*I), where T is the number of iterations, N the number of instances, I the number of features.

See: Y. Sun, Iterative RELIEF for Feature Weighting: Algorithms, Theories, and Applications, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 29, no. 6, pp. 1035-1051, June 2007. http://plaza.ufl.edu/sunyijun/Paper/PAMI_1.pdf

Note that current implementation allows to use only exponential-like kernels. Support for linear kernel will be added later.

Nested Classes [hide private]

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods [hide private]
 
__init__(self, threshold=1.0e-2, kernel=None, kernel_width=1.0, w_guess=None, **kwargs)
Constructor of the IRELIEF class.		 source code
 
compute_M_H(self, label)
Compute hit/miss dictionaries.		 source code
 
_call(self, dataset)
Computes featurewise I-RELIEF weights.		 source code

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 [hide private]

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 [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self, threshold=1.0e-2, kernel=None, kernel_width=1.0, w_guess=None, **kwargs)
(Constructor)

source code 
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__

compute_M_H(self, label)

source code 

Compute hit/miss dictionaries.

For each instance compute the set of indices having the same class label and different class label.

Note that this computation is independent of the number of features.

_call(self, dataset)

source code 
Computes featurewise I-RELIEF weights.
Overrides: base.DatasetMeasure._call

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PyMVPA: Python MultiVariate Pattern Analysis
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