add some scripts

AmirGeorge · May 27, 2016 · 5d7a9c2 · 5d7a9c2
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diff --git a/.gitignore b/.gitignore
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+/data/*
+Data
diff --git a/scripts/1-mimi0.61/New Text Document.txt b/scripts/1-mimi0.61/New Text Document.txt
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+
diff --git a/scripts/20-mimi0.68352/averagesUsageAvergaCountSlope0.68419.R b/scripts/20-mimi0.68352/averagesUsageAvergaCountSlope0.68419.R
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+# Amir's roaming data
+# Slope average and from month 1 to 5
+# Score0.68419
+
+library(dplyr)
+library(knitr)
+library(RWeka)
+
+RF <- make_Weka_classifier("weka/classifiers/trees/RandomForest")
+NB <- make_Weka_classifier("weka/classifiers/bayes/NaiveBayes")
+MLP <- make_Weka_classifier("weka/classifiers/functions/MultilayerPerceptron")
+
+trainDf <- read.csv('data/train.csv')
+testDf <- read.csv('data/test.csv')
+contractRefDf <- read.csv('data/contract_ref.csv')
+calendarRefDf <- read.csv('data/calendar_ref.csv')
+#dailyAggDf <- read.csv('data/daily_aggregate.csv')
+roamingDf <- read.csv('data/roaming_monthly.csv')
+
+trainDf$TARGET <- as.factor(trainDf$TARGET)
+
+
+trainRoamDf <- trainDf
+#prepare tain data
+trainRoamDf <- trainRoamDf %>% rowwise() %>% mutate(slope1to5 = (as.double(X210_USAGE)-as.double(X206_USAGE))/4, avg_usage = (X206_USAGE+X207_USAGE+X208_USAGE+X209_USAGE+X210_USAGE)/4,avg_sessions_count = (X206_SESSION_COUNT+X207_SESSION_COUNT+X208_SESSION_COUNT+X209_SESSION_COUNT+X210_SESSION_COUNT)/4
+   )
+
+testRoamDf <- testDf
+##prepare test data
+testRoamDf <- testRoamDf %>% rowwise() %>% mutate(slope1to5 = (as.double(X210_USAGE)-as.double(X206_USAGE))/4, avg_usage = (X206_USAGE+X207_USAGE+X208_USAGE+X209_USAGE+X210_USAGE)/4,
+  avg_sessions_count = (X206_SESSION_COUNT+X207_SESSION_COUNT+X208_SESSION_COUNT+X209_SESSION_COUNT+X210_SESSION_COUNT)/4
+   )
+
+trainRoamDf[,"R206_USAGE"] <- 0
+trainRoamDf[,"R206_SESSION_COUNT"] <- 0
+trainRoamDf[,"R207_USAGE"] <- 0
+trainRoamDf[,"R207_SESSION_COUNT"] <- 0
+trainRoamDf[,"R208_USAGE"] <- 0
+trainRoamDf[,"R208_SESSION_COUNT"] <- 0
+trainRoamDf[,"R209_USAGE"] <- 0
+trainRoamDf[,"R209_SESSION_COUNT"] <- 0
+trainRoamDf[,"R210_USAGE"] <- 0
+trainRoamDf[,"R210_SESSION_COUNT"] <- 0
+
+
+testRoamDf[,"R206_USAGE"] <- 0
+testRoamDf[,"R206_SESSION_COUNT"] <- 0
+testRoamDf[,"R207_USAGE"] <- 0
+testRoamDf[,"R207_SESSION_COUNT"] <- 0
+testRoamDf[,"R208_USAGE"] <- 0
+testRoamDf[,"R208_SESSION_COUNT"] <- 0
+testRoamDf[,"R209_USAGE"] <- 0
+testRoamDf[,"R209_SESSION_COUNT"] <- 0
+testRoamDf[,"R210_USAGE"] <- 0
+testRoamDf[,"R210_SESSION_COUNT"] <- 0
+
+for (k in unique(roamingDf$CONTRACT_KEY)) {
+  orig <- roamingDf[roamingDf$CONTRACT_KEY==k,]
+  if (trainRoamDf[trainRoamDf$CONTRACT_KEY==k,] %>% nrow > 0) {
+    val <- orig[orig$CALL_MONTH_KEY == 206,]
+    if (nrow(val) > 0) {
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R206_USAGE"] = val$USAGE
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R206_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- orig[orig$CALL_MONTH_KEY == 207,]
+    if (nrow(val) > 0) {
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R207_USAGE"] = val$USAGE
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R207_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- orig[orig$CALL_MONTH_KEY == 208,]
+    if (nrow(val) > 0) {
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R208_USAGE"] = val$USAGE
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R208_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- val[val$CALL_MONTH_KEY == 209,]
+    if (nrow(val) > 0) {
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R209_USAGE"] = val$USAGE
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R209_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- orig[orig$CALL_MONTH_KEY == 210,]
+    if (nrow(val) > 0) {
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R210_USAGE"] = val$USAGE
+      trainRoamDf[trainRoamDf$CONTRACT_KEY==k,"R210_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+  }
+  else {
+    val <- orig[orig$CALL_MONTH_KEY == 206,]
+    if (nrow(val) > 0) {
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R206_USAGE"] = val$USAGE
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R206_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- orig[orig$CALL_MONTH_KEY == 207,]
+    if (nrow(val) > 0) {
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R207_USAGE"] = val$USAGE
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R207_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- orig[orig$CALL_MONTH_KEY == 208,]
+    if (nrow(val) > 0) {
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R208_USAGE"] = val$USAGE
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R208_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- val[val$CALL_MONTH_KEY == 209,]
+    if (nrow(val) > 0) {
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R209_USAGE"] = val$USAGE
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R209_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+    val <- orig[orig$CALL_MONTH_KEY == 210,]
+    if (nrow(val) > 0) {
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R210_USAGE"] = val$USAGE
+      testRoamDf[testRoamDf$CONTRACT_KEY==k,"R210_SESSION_COUNT"] = val$SESSION_COUNT
+    }
+  }
+}
+
+trainRoamDf <- trainRoamDf %>% mutate(X206_SESSION_COUNT = X206_SESSION_COUNT - R206_SESSION_COUNT,
+                                      X206_USAGE = X206_USAGE - R206_USAGE,
+                                      X207_SESSION_COUNT = X207_SESSION_COUNT - R207_SESSION_COUNT,
+                                      X207_USAGE = X207_USAGE - R207_USAGE,
+                                      X208_SESSION_COUNT = X208_SESSION_COUNT - R208_SESSION_COUNT,
+                                      X208_USAGE = X208_USAGE - R208_USAGE,
+                                      X209_SESSION_COUNT = X209_SESSION_COUNT - R209_SESSION_COUNT,
+                                      X209_USAGE = X209_USAGE - R209_USAGE,
+                                      X210_SESSION_COUNT = X210_SESSION_COUNT - R210_SESSION_COUNT,
+                                      X210_USAGE = X210_USAGE - R210_USAGE)
+
+testRoamDf <- testRoamDf %>% mutate(X206_SESSION_COUNT = X206_SESSION_COUNT - R206_SESSION_COUNT,
+                                      X206_USAGE = X206_USAGE - R206_USAGE,
+                                      X207_SESSION_COUNT = X207_SESSION_COUNT - R207_SESSION_COUNT,
+                                      X207_USAGE = X207_USAGE - R207_USAGE,
+                                      X208_SESSION_COUNT = X208_SESSION_COUNT - R208_SESSION_COUNT,
+                                      X208_USAGE = X208_USAGE - R208_USAGE,
+                                      X209_SESSION_COUNT = X209_SESSION_COUNT - R209_SESSION_COUNT,
+                                      X209_USAGE = X209_USAGE - R209_USAGE,
+                                      X210_SESSION_COUNT = X210_SESSION_COUNT - R210_SESSION_COUNT,
+                                      X210_USAGE = X210_USAGE - R210_USAGE)
+
+
+
+myModel <- MLP(TARGET~X206_SESSION_COUNT + X206_USAGE + 
+                 X207_SESSION_COUNT + X207_USAGE + 
+                 X208_SESSION_COUNT + X208_USAGE + 
+                 X209_SESSION_COUNT + X209_USAGE + 
+                 X210_SESSION_COUNT + X210_USAGE +
+                 R206_SESSION_COUNT + R206_USAGE + 
+                 R207_SESSION_COUNT + R207_USAGE + 
+                 R208_SESSION_COUNT + R208_USAGE + 
+                 R209_SESSION_COUNT + R209_USAGE + 
+                 R210_SESSION_COUNT + R210_USAGE+
+
+                                avg_usage+avg_sessions_count+slope1to5
+                            , data=trainRoamDf)
+myTarget = predict(myModel, newdata = testRoamDf, type="class")
+myResult <- data.frame(CONTRACT_KEY=testRoamDf$CONTRACT_KEY, PREDICTED_TARGET=myTarget)
+write.table(myResult, file="averagesUsageAvergaCountSlope.csv", sep =",", row.names= FALSE)