jch 4 ヶ月 前
コミット
672c1c27bf

+ 10 - 0
recommend-model-produce/src/main/scala/com/tzld/piaoquan/recommend/model/pred_recsys_61_xgb_nor_hdfsfile_20241209.scala

@@ -84,7 +84,9 @@ object pred_recsys_61_xgb_nor_hdfsfile_20241209 {
       .setPredictionCol("prediction")
       .setMetricName("rmse")
     val rmse = evaluator.evaluate(predictions.select("label", "prediction"))
+    val rmsle = calRMSLE(predictions.select("label", "prediction").rdd)
     println("recsys rov:rmse:" + rmse)
+    println("recsys nor: rmsle:" + rmsle)
 
     println("---------------------------------\n")
     println("---------------------------------\n")
@@ -109,4 +111,12 @@ object pred_recsys_61_xgb_nor_hdfsfile_20241209 {
     })
   }
 
+  def calRMSLE(evalRdd: RDD[Row]): Double = {
+    val sleRdd = evalRdd.map(raw => {
+      val label = raw.get(0).toString.toDouble
+      val pred = raw.get(1).toString.toDouble
+      math.pow(math.log(pred + 1) - math.log(label + 1), 2)
+    })
+    sleRdd.sum() / sleRdd.count()
+  }
 }

+ 1 - 11
recommend-model-produce/src/main/scala/com/tzld/piaoquan/recommend/model/train_recsys_61_xgb_nor_20241209.scala

@@ -123,9 +123,8 @@ object train_recsys_61_xgb_nor_20241209 {
         .setPredictionCol("prediction")
         .setMetricName("rmse")
       val rmse = evaluator.evaluate(predictions.select("label", "prediction"))
-      val rmsle = calRMSLE(predictions.select("label", "prediction").rdd)
       println("recsys nor: rmse:" + rmse)
-      println("recsys nor: rmsle:" + rmsle)
+
     }
   }
 
@@ -147,13 +146,4 @@ object train_recsys_61_xgb_nor_20241209 {
       Row(v: _*)
     })
   }
-
-  def calRMSLE(evalRdd: RDD[Row]): Double = {
-    val sleRdd = evalRdd.map(raw => {
-      val label = raw.get(0).toString.toDouble
-      val pred = raw.get(1).toString.toDouble
-      math.pow(math.log(pred + 1) - math.log(label + 1), 2)
-    })
-    sleRdd.sum() / sleRdd.count()
-  }
 }