Mf_fit (models.mf_fit)¶
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class
nimfa.models.mf_fit.Mf_fit(fit)¶ Base class for storing MF results.
It contains generic functions and structure for handling the results of MF algorithms. It contains a slot with the fitted MF model and data about parameters and methods used for factorization.
The purpose of this class is to handle in a generic way the results of MF algorithms and acts as a wrapper for the fitted model. Its attribute attribute:: fit contains the fitted model and its configuration can therefore be used directly in following calls to factorization.
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fit¶ The fitted NMF model
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algorithm¶ NMF method of factorization.
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n_iter¶ The number of iterations performed.
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n_run¶ The number of NMF runs performed.
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seeding¶ The seeding method used to seed the algorithm that fitted NMF model.
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options¶ Extra parameters specific to the algorithm used to fit the model.
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basis()¶ Return the matrix of basis vectors.
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coef(idx=None)¶ Return the matrix of mixture coefficients.
Parameters: idx (str with values ‘coef’ or ‘coef1’ (int value of 0 or 1, respectively)) – Name of the matrix (coefficient) matrix. Used only in the multiple NMF model.
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distance(metric=None, idx=None)¶ Return the loss function value. If metric is not supplied, final objective function value associated to the MF algorithm is returned.
Parameters: - metric ('str') – Measure of distance between a target matrix and a MF estimate. Metric ‘kl’ and ‘euclidean’ are defined.
- idx (str with values ‘coef’ or ‘coef1’ (int value of 0 or 1, respectively)) – Name of the matrix (coefficient) matrix. Used only in the multiple NMF model.
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fit() Return the MF algorithm model.
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fitted(idx=None)¶ Compute the estimated target matrix according to the MF algorithm model.
Parameters: idx (str with values ‘coef’ or ‘coef1’ (int value of 0 or 1, respectively)) – Name of the matrix (coefficient) matrix. Used only in the multiple NMF model.
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summary(idx=None)¶ Return generic set of measures to evaluate the quality of the factorization.
Parameters: idx (str with values ‘coef’ or ‘coef1’ (int value of 0 or 1, respectively)) – Name of the matrix (coefficient) matrix. Used only in the multiple NMF model.
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