Json

README.md

@@ -10,7 +10,7 @@ Should be available by default on the IC Cluster. Otherwise, refer to each proje
 
 Download the ````ml-100k.zip```` dataset in the ````data/```` folder:
 ````
-> mkdir data
+> mkdir -p data
 > cd data
 > wget http://files.grouplens.org/datasets/movielens/ml-100k.zip   
 ````

src/main/scala/predict/Predictor.scala

@@ -65,9 +65,36 @@ object Predictor extends App {
         // Limiting the scope of implicit formats with {}
         implicit val formats = org.json4s.DefaultFormats
         val answers: Map[String, Any] = Map(
-           "3.1.4" -> Map(
-             "global-mae" -> globalMae
-           )
+            "Q3.1.4" -> Map(
+              "MaeGlobalMethod" -> 0.0, // Datatype of answer: Double
+              "MaePerUserMethod" -> 0.0, // Datatype of answer: Double
+              "MaePerItemMethod" -> 0.0, // Datatype of answer: Double
+              "MaeBaselineMethod" -> 0.0 // Datatype of answer: Double
+            ),
+
+            "Q3.1.5" -> Map(
+              "DurationInMicrosecForGlobalMethod" -> Map(
+                "min" -> 0.0,  // Datatype of answer: Double
+                "max" -> 0.0,  // Datatype of answer: Double
+                "average" -> 0.0 // Datatype of answer: Double
+              ),
+              "DurationInMicrosecForPerUserMethod" -> Map(
+                "min" -> 0.0,  // Datatype of answer: Double
+                "max" -> 0.0,  // Datatype of answer: Double
+                "average" -> 0.0 // Datatype of answer: Double
+              ),
+              "DurationInMicrosecForPerItemMethod" -> Map(
+                "min" -> 0.0,  // Datatype of answer: Double
+                "max" -> 0.0,  // Datatype of answer: Double
+                "average" -> 0.0 // Datatype of answer: Double
+              ),
+              "DurationInMicrosecForBaselineMethod" -> Map(
+                "min" -> 0.0,  // Datatype of answer: Double
+                "max" -> 0.0, // Datatype of answer: Double
+                "average" -> 0.0 // Datatype of answer: Double
+              ),
+              "RatioBetweenBaselineMethodAndGlobalMethod" -> 0.0 // Datatype of answer: Double
+            ),
          )
         json = Serialization.writePretty(answers)
       }

src/main/scala/recommend/Recommender.scala

@@ -61,13 +61,18 @@ object Recommender extends App {
         // Limiting the scope of implicit formats with {}
         implicit val formats = org.json4s.DefaultFormats
         val answers: Map[String, Any] = Map(
-           "4.1.1" -> List[Any](
-             List(0,"Tron", 5.0),
-             List(0,"Tron", 5.0),
-             List(0,"Tron", 5.0),
-             List(0,"Tron", 5.0),
-             List(0,"Tron", 5.0)
-           )
+
+            // IMPORTANT: To break ties and ensure reproducibility of results,
+            // please report the top-5 recommendations that have the smallest
+            // movie identifier.
+
+            "Q4.1.1" -> List[Any](
+              List(254, "Batman & Robin (1997)", 5.0), // Datatypes for answer: Int, String, Double
+              List(338, "Bean (1997)", 5.0),
+              List(615, "39 Steps", 5.0),
+              List(741, "Last Supper", 5.0),
+              List(587, "Hour of the Pig", 5.0)
+            )
          )
         json = Serialization.writePretty(answers)
       }

src/main/scala/stats/Analyzer.scala

@@ -53,9 +53,31 @@ object Analyzer extends App {
         // Limiting the scope of implicit formats with {}
         implicit val formats = org.json4s.DefaultFormats
         val answers: Map[String, Any] = Map(
-           "3.1.1" -> Map(
-             "global-avg-rating" -> 3.0
-           )
+          "Q3.1.1" -> Map(
+            "GlobalAverageRating" -> 0.0 // Datatype of answer: Double
+          ),
+          "Q3.1.2" -> Map(
+            "UsersAverageRating" -> Map(
+                // Using as your input data the average rating for each user,
+                // report the min, max and average of the input data.
+                "min" -> 0.0,  // Datatype of answer: Double
+                "max" -> 0.0, // Datatype of answer: Double
+                "average" -> 0.0 // Datatype of answer: Double
+            ),
+            "AllUsersCloseToGlobalAverageRating" -> true, // Datatype of answer: Boolean
+            "RatioUsersCloseToGlobalAverageRating" -> 0.0 // Datatype of answer: Double
+          ),
+          "Q3.1.3" -> Map(
+            "ItemsAverageRating" -> Map(
+                // Using as your input data the average rating for each item,
+                // report the min, max and average of the input data.
+                "min" -> 0.0,  // Datatype of answer: Double
+                "max" -> 0.0, // Datatype of answer: Double
+                "average" -> 0.0 // Datatype of answer: Double
+            ),
+            "AllItemsCloseToGlobalAverageRating" -> true, // Datatype of answer: Boolean
+            "RatioItemsCloseToGlobalAverageRating" -> 0.0 // Datatype of answer: Double
+          ),
          )
         json = Serialization.writePretty(answers)
       }