Remove obsolete files
diff --git a/src/main/scala/PopularAlgorithm.scala b/src/main/scala/PopularAlgorithm.scala
deleted file mode 100644
index c4255bc..0000000
--- a/src/main/scala/PopularAlgorithm.scala
+++ /dev/null
@@ -1,72 +0,0 @@
-package org.template.ecommercerecommendation
-/*
-import io.prediction.controller.P2LAlgorithm
-import io.prediction.controller.Params
-
-
-case class PopularAlgorithmParams() extends Params
-
-class PopularModel(
- val itemModel: Vector[(String, (Item, Int))] // Vector of (item ID, (Item, Count))
-) extends Serializable {
-
-}
-
-class PopularAlgorithm(val ap: PopularAlgorithmParams)
- extends P2LAlgorithm[PreparedData, PopularModel, Query, PredictedResult] {
-
-
- def train(sc: SparkContext, data: PreparedData): PopularModel = {
-
- // calculate number of buys for each item
- val buyCounts: RDD[(String, Int)] = data.buyEvents
- .map { buy => (buy.item, 1) }
- .reduceByKey{ case (a, b) => a + b }
-
- // combine item data with the count
- val itemWithCount: RDD[(String, (Item, Int))] = data.items.join(buyCounts)
-
- // collect to local vector, and sort save as model
- val itemModel = itemWithCount.collect.toVector
- .sortBy{ case (id, (item, count)) => count }(Ordering.Int.revese)
-
- PopularModel(
- itemModel = itemModel
- )
-
- }
-
-
- def predict(model: PopularModel, query: Query): PredictedResult = {
- model.itemModel.filter {
- case (id, (item, count)) =>
- isCandidateItem(
-
- )
- )
- }
- }
-
- private
- def isCandidateItem(
- i: Int,
- item: Item,
- categories: Option[Set[String]],
- whiteList: Option[Set[Int]],
- blackList: Set[Int]
- ): Boolean = {
- // can add other custom filtering here
- whiteList.map(_.contains(i)).getOrElse(true) &&
- !blackList.contains(i) &&
- // filter categories
- categories.map { cat =>
- item.categories.map { itemCat =>
- // keep this item if has ovelap categories with the query
- !(itemCat.toSet.intersect(cat).isEmpty)
- }.getOrElse(false) // discard this item if it has no categories
- }.getOrElse(true)
-
- }
-
-}
-*/
