Source code for

.. module:: CClassifierReject
   :synopsis: Interface and common functions for classification with rejection

.. moduleauthor:: Ambra Demontis <>

from abc import abstractmethod, ABCMeta

from import CClassifier

[docs]class CClassifierReject(CClassifier, metaclass=ABCMeta): """Abstract class that defines basic methods for Classifiers with reject. A classifier assign a label (class) to new patterns using the information learned from training set. This interface implements a set of generic methods for training and classification that can be used for every algorithms. However, all of them can be reimplemented if specific routines are needed. Parameters ---------- preprocess : str or CNormalizer Features preprocess to applied to input data. Can be a CNormalizer subclass or a string with the desired preprocess type. If None, input data is used as is. """ __super__ = 'CClassifierReject'
[docs] @abstractmethod def predict(self, x, return_decision_function=False, n_jobs=1): """Perform classification of each pattern in x. If a preprocess has been specified, input is normalized before classification. Parameters ---------- x : CArray Array with new patterns to classify, 2-Dimensional of shape (n_patterns, n_features). return_decision_function : bool, optional Whether to return the decision_function value along with predictions. Default False. n_jobs : int, optional Number of parallel workers to use for classification. Default 1. Cannot be higher than processor's number of cores. Returns ------- labels : CArray Flat dense array of shape (n_patterns,) with the label assigned to each test pattern. The classification label is the label of the class associated with the highest score. The rejected samples have label -1. scores : CArray, optional Array of shape (n_patterns, n_classes) with classification score of each test pattern with respect to each training class. Will be returned only if `return_decision_function` is True. """ raise NotImplementedError
def _check_clf_index(self, y): """Raise error if index y is outside [-1, n_classes) range. Parameters ---------- y : int class label index. """ if y < -1 or y >= self.n_classes: raise ValueError( "class label {:} is out of range".format(y))