Package mvpa :: Package measures :: Module irelief :: Class IterativeRelief

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# Class IterativeRelief

source code

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

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_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

k(self, distances) Exponential kernel. | 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_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.

XXX should it be some generic function since it doesn't use self

### _call(self, dataset)

source code

Computes featurewise I-RELIEF weights.

Overrides: base.DatasetMeasure._call