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Open Source Chemistry Library
/*******************************************************************************
* 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.regression;
import java.io.Serializable;
/**
* Regression analysis includes any techniques for modeling and analyzing
* the relationship between a dependent variable and one or more independent
* variables. Most commonly, regression analysis estimates the conditional
* expectation of the dependent variable given the independent variables.
* Regression analysis is widely used for prediction and forecasting, where
* its use has substantial overlap with the field of machine learning.
*
* @author Haifeng Li
*/
public interface Regression extends Serializable {
/**
* Predicts the dependent variable of an instance.
* @param x the instance.
* @return the predicted value of dependent variable.
*/
double predict(T x);
/**
* Predicts the dependent variables of an array of instances.
*
* @param x the instances.
* @return the predicted values.
*/
default double[] predict(T[] x) {
double[] y = new double[x.length];
for (int i = 0; i < y.length; i++) {
y[i] = predict(x[i]);
}
return y;
}
}