rename Evaluator to Metrics and add more metrics

Author: mengxr

mllib/src/main/scala/org/apache/spark/mllib/evaluation/binary/BinaryClassificationEvaluator.scala

@@ -0,0 +1,57 @@
+/*
+ * 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.spark.mllib.evaluation.binary
+
+/**
+ * Trait for a binary classification evaluation metric computer.
+ */
+private[evaluation] trait BinaryClassificationMetricComputer extends Serializable {
+  def apply(c: BinaryConfusionMatrix): Double
+}
+
+/** Precision. */
+private[evaluation] object Precision extends BinaryClassificationMetricComputer {
+  override def apply(c: BinaryConfusionMatrix): Double =
+    c.tp.toDouble / (c.tp + c.fp)
+}
+
+/** False positive rate. */
+private[evaluation] object FalsePositiveRate extends BinaryClassificationMetricComputer {
+  override def apply(c: BinaryConfusionMatrix): Double =
+    c.fp.toDouble / c.n
+}
+
+/** Recall. */
+private[evaluation] object Recall extends BinaryClassificationMetricComputer {
+  override def apply(c: BinaryConfusionMatrix): Double =
+    c.tp.toDouble / c.p
+}
+
+/**
+ * F-Measure.
+ * @param beta the beta constant in F-Measure
+ * @see http://en.wikipedia.org/wiki/F1_score
+ */
+private[evaluation] case class FMeasure(beta: Double) extends BinaryClassificationMetricComputer {
+  private val beta2 = beta * beta
+  override def apply(c: BinaryConfusionMatrix): Double = {
+    val precision = Precision(c)
+    val recall = Recall(c)
+    (1.0 + beta2) * (precision * recall) / (beta2 * precision + recall)
+  }
+}