Demonstrates how to randomly sort a collection of elements, where each class may have a different weight (all weights must be non-negative and sum to 1.0)

WeightedRandomTest.java

import java.util.Map;
import java.util.HashMap;

public class WeightedRandomTest {
	private static final int NUM_CLASSIFICATIONS = 1_000_000;

	private static Classification classify() {
		double factor = Math.random();
		for (final Classification classification : Classification.values()) {
			factor -= classification.getWeight();
			if (factor <= 0.0) {
				return classification;
			}
		}
		return null;
	}

	public static void main(final String[] args) {
		final Map<Classification, Integer> histogram = new HashMap<>();
		for (final Classification classification : Classification.values()) {
			histogram.put(classification, 0);
		}
		for (int i = 0; i < NUM_CLASSIFICATIONS; ++i) {
			final Classification classification = classify();
			histogram.put(classification, 1 + histogram.get(classification));
		}
		for (final Classification classification : Classification.values()) {
			System.out.printf("%s{expected=%.5f, actual=%.5f}\n",
					classification,
					classification.getWeight(),
					(double) histogram.get(classification) / NUM_CLASSIFICATIONS);
		}
	}

	private enum Classification {
		TRAIN(0.60),
		TEST(0.20),
		CROSS_VALIDATION(0.20);

		private final double weight;

		private Classification(final double weight) {
			this.weight = weight;
		}

		public double getWeight() {
			return weight;
		}
	}
}

Sample output:

TRAIN{expected=0.60000, actual=0.60054}
TEST{expected=0.20000, actual=0.19918}
CROSS_VALIDATION{expected=0.20000, actual=0.20028}