diff --git a/.gitignore b/.gitignore
index 7c6771b..66a5d40 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,4 +1,3 @@
-data/*.txt
 manifest.json
 pio.log
 /pio.sbt
diff --git a/README.md b/README.md
index ebdf31a..b4f7cd7 100644
--- a/README.md
+++ b/README.md
@@ -6,6 +6,12 @@
 
 ## Versions
 
+### v0.1.4
+
+- Update Evaluation for PredictionIO 0.9.1
+
+NOTE: Require PredictionIO >= 0.9.1
+
 ### v0.1.3
 
 - Add missing sample data set (data/data.txt)
diff --git a/src/main/scala/CompleteEvaluation.scala b/src/main/scala/CompleteEvaluation.scala
new file mode 100644
index 0000000..e168872
--- /dev/null
+++ b/src/main/scala/CompleteEvaluation.scala
@@ -0,0 +1,13 @@
+package org.template.classification
+
+import io.prediction.controller.Evaluation
+import io.prediction.controller.MetricEvaluator
+
+object CompleteEvaluation extends Evaluation {
+  engineEvaluator = (
+    ClassificationEngine(),
+    MetricEvaluator(
+      metric = Accuracy(),
+      otherMetrics = Seq(Precision(0.0), Precision(1.0), Precision(2.0)),
+      outputPath = "best.json"))
+}
diff --git a/src/main/scala/Evaluation.scala b/src/main/scala/Evaluation.scala
index 8a903ee..ec8e16c 100644
--- a/src/main/scala/Evaluation.scala
+++ b/src/main/scala/Evaluation.scala
@@ -5,21 +5,16 @@
 import io.prediction.controller.EngineParams
 import io.prediction.controller.EngineParamsGenerator
 import io.prediction.controller.Evaluation
-import io.prediction.controller.Workflow
-import org.apache.spark.SparkContext
-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 +24,7 @@
   // 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
diff --git a/src/main/scala/PrecisionEvaluation.scala b/src/main/scala/PrecisionEvaluation.scala
new file mode 100644
index 0000000..de80b76
--- /dev/null
+++ b/src/main/scala/PrecisionEvaluation.scala
@@ -0,0 +1,27 @@
+package org.template.classification
+
+import io.prediction.controller.OptionAverageMetric
+import io.prediction.controller.EmptyEvaluationInfo
+import io.prediction.controller.Evaluation
+
+case class Precision(label: Double)
+  extends OptionAverageMetric[EmptyEvaluationInfo, Query, PredictedResult, ActualResult] {
+  override def header: String = s"Precision(label = $label)"
+
+  def calculate(query: Query, predicted: PredictedResult, actual: ActualResult)
+  : Option[Double] = {
+    if (predicted.label == label) {
+      if (predicted.label == actual.label) {
+        Some(1.0)  // True positive
+      } else {
+        Some(0.0)  // False positive
+      }
+    } else {
+      None  // Unrelated case for calcuating precision
+    }
+  }
+}
+
+object PrecisionEvaluation extends Evaluation {
+  engineMetric = (ClassificationEngine(), new Precision(label = 1.0))
+}
diff --git a/template.json b/template.json
index 932e603..e617464 100644
--- a/template.json
+++ b/template.json
@@ -1 +1 @@
-{"pio": {"version": { "min": "0.9.0" }}}
+{"pio": {"version": { "min": "0.9.1" }}}