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A Java implementation of the Apriori algorithm for finding frequent item sets and (optionally) generating association rules.

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/*
 * Copyright 2017 - 2019 Michael Rapp
 *
 * 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 de.mrapp.apriori.metrics

import de.mrapp.apriori.AssociationRule
import de.mrapp.apriori.Metric

/**
 * A metric, which measures the support of an association rule. By definition, support measures the
 * percentage of transactions for which the body and head of the rule is true.
 *
 * @author Michael Rapp
 * @since 1.0.0
 */
class Support : Metric {

    override fun evaluate(rule: AssociationRule<*>) = rule.support

    override fun minValue() = 0.0

    override fun maxValue() = 1.0

}




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