/*******************************************************************************
* Copyright (c) 2010 Haifeng Li
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
package smile.classification;
/**
* A classifier assigns an input object into one of a given number of categories.
* The input object is formally termed an instance, and the categories are
* termed classes. The instance is usually described by a vector of features,
* which together constitute a description of all known characteristics of the
* instance.
* <p>
* Classification normally refers to a supervised procedure, i.e. a procedure
* that produces an inferred function to predict the output value of new
* instances based on a training set of pairs consisting of an input object
* and a desired output value. The inferred function is called a classifier
* if the output is discrete or a regression function if the output is
* continuous.
*
* @param <T> the type of input object
*
* @author Haifeng Li
*/
public interface Classifier<T> {
/**
* Predicts the class label of an instance.
*
* @param x the instance to be classified.
* @return the predicted class label
*/
public int predict(T x);
}