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JKernelMachines is a java library for learning with kernels. It is primary
designed to deal with custom kernels that are not easily found in standard
libraries, such as kernels on structured data.
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/*******************************************************************************
* Copyright (c) 2016, David Picard.
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation and/or
* other materials provided with the distribution.
*
* 3. Neither the name of the copyright holder nor the names of its contributors
* may be used to endorse or promote products derived from this software without
* specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
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* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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*******************************************************************************/
package net.jkernelmachines.classifier;
import java.util.List;
import net.jkernelmachines.type.TrainingSample;
/**
* Classifier interface that provides training and evaluation methods.
* @author dpicard
*
* @param inputspace datatype
*/
public interface Classifier extends Cloneable {
/**
* Replace the current training list and train the classifier
* @param l list of training samples
*/
public void train(List> l);
/**
* Computes the category of the provided example
* @param e example
* @return > 0. if e belongs to the category, < 0. if not.
*/
public double valueOf(T e);
/**
* Creates and returns a copy of this object.
* @see java.lang.Object#clone()
* @return a copy of this object
* @throws CloneNotSupportedException if class not clonable
*/
public Classifier copy() throws CloneNotSupportedException;
}