diff --git a/engine.json b/engine.json
index da6bd9c..05c8440 100644
--- a/engine.json
+++ b/engine.json
@@ -9,7 +9,8 @@
   },
   "preparator": {
     "params": {
-      "nGram": 2
+      "nGram": 2,
+      "numFeatures": 15000
     }
   },
   "algorithms": [
diff --git a/src/main/scala/org/template/textclassification/NBAlgorithm.scala b/src/main/scala/org/template/textclassification/NBAlgorithm.scala
index 512c2e9..1c1c31d 100644
--- a/src/main/scala/org/template/textclassification/NBAlgorithm.scala
+++ b/src/main/scala/org/template/textclassification/NBAlgorithm.scala
@@ -65,6 +65,8 @@
 
 
 
+  private val scoreArray = nb.pi.zip(nb.theta)
+
   // 3. Given a document string, return a vector of corresponding
   // class membership probabilities.
 
@@ -75,12 +77,7 @@
     // Vectorize query,
     val x: Vector = pd.transform(doc)
 
-    normalize(
-      nb.pi
-      .zip(nb.theta)
-      .map(
-      e => exp(innerProduct(e._2, x.toArray) + e._1))
-    )
+    normalize(scoreArray.map(e => exp(innerProduct(e._2, x.toArray) + e._1)))
   }
 
   // 4. Implement predict method for our model using
diff --git a/src/main/scala/org/template/textclassification/Preparator.scala b/src/main/scala/org/template/textclassification/Preparator.scala
index 871b7e4..badc49c 100644
--- a/src/main/scala/org/template/textclassification/Preparator.scala
+++ b/src/main/scala/org/template/textclassification/Preparator.scala
@@ -20,7 +20,8 @@
 // components.
 
 case class PreparatorParams(
-  nGram : Int
+  nGram : Int,
+  numFeatures: Int = 15000
 ) extends Params
 
 
@@ -31,22 +32,23 @@
 
   // Prepare your training data.
   def prepare(sc : SparkContext, td: TrainingData): PreparedData = {
-    new PreparedData(td, pp.nGram)
+    new PreparedData(td, pp.nGram, pp.numFeatures)
   }
 }
 
 //------PreparedData------------------------
 
 class PreparedData (
-val td : TrainingData,
-val nGram : Int
+  val td : TrainingData,
+  val nGram : Int,
+  val numFeatures: Int
 ) extends Serializable {
 
 
 
   // 1. Hashing function: Text -> term frequency vector.
 
-  private val hasher = new HashingTF()
+  private val hasher = new HashingTF(numFeatures = numFeatures)
 
   private def hashTF (text : String) : Vector = {
     val newList : Array[String] = text.split(" ")