Eval for 0.9.1
diff --git a/build.sbt b/build.sbt
index a7e7858..0115703 100644
--- a/build.sbt
+++ b/build.sbt
@@ -7,6 +7,7 @@
organization := "io.prediction"
libraryDependencies ++= Seq(
- "io.prediction" %% "core" % pioVersion.value % "provided",
+ //"io.prediction" %% "core" % pioVersion.value % "provided",
+ "io.prediction" %% "core" % "0.9.1-SNAPSHOT" % "provided",
"org.apache.spark" %% "spark-core" % "1.2.0" % "provided",
"org.apache.spark" %% "spark-mllib" % "1.2.0" % "provided")
diff --git a/src/main/scala/Evaluation.scala b/src/main/scala/Evaluation.scala
index 8a903ee..a635b93 100644
--- a/src/main/scala/Evaluation.scala
+++ b/src/main/scala/Evaluation.scala
@@ -10,16 +10,15 @@
import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD
-case class Precision
- extends AverageMetric[EmptyEvaluationInfo,
- Query, PredictedResult, ActualResult] {
+case class Accuracy
+ extends AverageMetric[EmptyEvaluationInfo, Query, PredictedResult, ActualResult] {
def calculate(query: Query, predicted: PredictedResult, actual: ActualResult)
: Double = (if (predicted.label == actual.label) 1.0 else 0.0)
}
-object PrecisionEvaluation extends Evaluation {
+object AccuracyEvaluation extends Evaluation {
// Define Engine and Metric used in Evaluation
- engineMetric = (ClassificationEngine(), new Precision())
+ engineMetric = (ClassificationEngine(), new Accuracy())
}
object EngineParamsList extends EngineParamsGenerator {
@@ -29,7 +28,7 @@
// the data is read, and a evalK parameter is used to define the
// cross-validation.
private[this] val baseEP = EngineParams(
- dataSourceParams = DataSourceParams(appId = 18, evalK = Some(5)))
+ dataSourceParams = DataSourceParams(appId = 19, evalK = Some(5)))
// Second, we specify the engine params list by explicitly listing all
// algorithm parameters. In this case, we evaluate 3 engine params, each with
