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A Java's Collaborative Filtering library to carry out experiments in research of Collaborative Filtering based Recommender Systems. The library has been designed from researchers to researchers.

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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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 org.apache.commons.math3.stat.descriptive;

import org.apache.commons.math3.exception.MathIllegalArgumentException;

/**
 * Weighted evaluation for statistics.
 *
 * @since 2.1
 */
public interface WeightedEvaluation {

    /**
     * Returns the result of evaluating the statistic over the input array,
     * using the supplied weights.
     *
     * @param values input array
     * @param weights array of weights
     * @return the value of the weighted statistic applied to the input array
     * @throws MathIllegalArgumentException if either array is null, lengths
     * do not match, weights contain NaN, negative or infinite values, or
     * weights does not include at least on positive value
     */
    double evaluate(double[] values, double[] weights) throws MathIllegalArgumentException;

    /**
     * Returns the result of evaluating the statistic over the specified entries
     * in the input array, using corresponding entries in the supplied weights array.
     *
     * @param values the input array
     * @param weights array of weights
     * @param begin the index of the first element to include
     * @param length the number of elements to include
     * @return the value of the weighted statistic applied to the included array entries
     * @throws MathIllegalArgumentException if either array is null, lengths
     * do not match, indices are invalid, weights contain NaN, negative or
     * infinite values, or weights does not include at least on positive value
     */
    double evaluate(double[] values, double[] weights, int begin, int length)
    throws MathIllegalArgumentException;

}