Created
August 27, 2014 02:44
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package org.deeplearning4j.nn.api; | |
import org.deeplearning4j.linalg.api.ndarray.INDArray; | |
/** | |
* A classifier (this is for supervised learning) | |
* | |
* @author Adam Gibson | |
*/ | |
public interface Classifier { | |
/** | |
* Returns the amount of error for each example | |
* @param examples te the examples to classify (one example in each row) | |
* @param labels the true labels | |
* @return the scores for each ndarray | |
*/ | |
float[] score(INDArray examples,INDArray labels); | |
/** | |
* Returns the number of possible labels | |
* @return the number of possible labels for this classifier | |
*/ | |
int numLabels(); | |
/** | |
* Takes in a list of examples | |
* For each row, returns a label | |
* @param examples the examples to classify (one example in each row) | |
* @return the labels for each example | |
*/ | |
int[] predict(INDArray examples); | |
/** | |
* Returns the probabilities for each label | |
* for each example row wise | |
* @param examples the examples to classify (one example in each row) | |
* @return the likelihoods of each example and each label | |
*/ | |
INDArray labelProbabilites(INDArray examples); | |
/** | |
* Fit the model | |
* @param examples the examples to classify (one example in each row) | |
* @param labels the example labels(a binary outcome matrix) | |
*/ | |
void fit(INDArray examples,INDArray labels); | |
/** | |
* Fit the model | |
* @param examples the examples to classify (one example in each row) | |
* @param labels the labels for each example (the number of labels must match | |
* the number of rows in the example | |
*/ | |
void fit(INDArray examples,int[] labels); | |
} |
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