com.cloudera.oryx.rdf.common.rule.NumericPrediction.java Source code

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Here is the source code for com.cloudera.oryx.rdf.common.rule.NumericPrediction.java

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/*
 * Copyright (c) 2013, Cloudera, Inc. All Rights Reserved.
 *
 * Cloudera, Inc. 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
 *
 * This software 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 com.cloudera.oryx.rdf.common.rule;

import com.google.common.base.Preconditions;
import org.apache.commons.math3.stat.descriptive.StorelessUnivariateStatistic;
import org.apache.commons.math3.stat.descriptive.moment.Mean;

import com.cloudera.oryx.rdf.common.example.Example;
import com.cloudera.oryx.rdf.common.example.FeatureType;
import com.cloudera.oryx.rdf.common.example.NumericFeature;

/**
 * Represents a predicted value of a numeric target. The prediction is simply a real number in this case.
 *
 * @author Sean Owen
 * @see CategoricalPrediction
 */
public final class NumericPrediction extends Prediction {

    private float prediction;

    public NumericPrediction(float prediction, int initialCount) {
        super(initialCount);
        this.prediction = prediction;
    }

    public float getPrediction() {
        return prediction;
    }

    @Override
    public FeatureType getFeatureType() {
        return FeatureType.NUMERIC;
    }

    @Override
    public synchronized void update(Example train) {
        NumericFeature target = (NumericFeature) train.getTarget();
        int oldCount = getCount();
        int newCount = oldCount + 1;
        setCount(newCount);
        prediction = (float) ((oldCount / (double) newCount) * prediction + target.getValue() / (double) newCount);
    }

    @Override
    public boolean equals(Object o) {
        if (!(o instanceof NumericPrediction)) {
            return false;
        }
        NumericPrediction other = (NumericPrediction) o;
        return prediction == other.prediction;
    }

    @Override
    public int hashCode() {
        return Float.floatToIntBits(prediction);
    }

    @Override
    public String toString() {
        return Float.toString(prediction);
    }

    static NumericPrediction buildNumericPrediction(Iterable<Example> examples) {
        StorelessUnivariateStatistic mean = new Mean();
        for (Example example : examples) {
            mean.increment(((NumericFeature) example.getTarget()).getValue());
        }
        Preconditions.checkState(mean.getN() > 0);
        return new NumericPrediction((float) mean.getResult(), (int) mean.getN());
    }

}