Commit 0a18f092 by Weigert, Andreas

changed folds to 10

`added t.test example`
parent bd968404
 ... ... @@ -62,6 +62,7 @@ household <- 8 plot(ts(smd[household,], frequency = 4*24), main="Weekly load curve") #plot the monday plot(ts(smd[household,1:(24*4)], frequency = 4), main="Load curves for each day") ... ... @@ -90,7 +91,7 @@ calcFeatures.smd <- function(SMD){ # define some times weekday <- 1:(5*4*24) weekend <- (5*4*24+1):672 night <- ( 1*4+1):( 6*4) night <- ( 1*4+1):(6*4) morning <- ( 6*4+1):(10*4) noon <- (10*4+1):(14*4) afternoon <- (14*4+1):(18*4) ... ...
 ... ... @@ -137,12 +137,15 @@ plot(performance(pred, "tpr", "fpr")) ```{r Classification with an advanced evaluation technique: cross-validation} set.seed(1506) all_data\$crossfolds <- sample(1:5, nrow(all_data), replace = TRUE) folds <- 10 all_data\$crossfolds <- sample(1:folds, nrow(all_data), replace = TRUE) # list for the interim results results <- list() for(foldIndex in 1:5){ for(foldIndex in 1:folds){ # creating data for the testdata <- na.omit(all_data[all_data\$crossfolds==foldIndex, c("pNumResidents2", selected.features)]) traindata <- na.omit(all_data[all_data\$crossfolds!=foldIndex, c("pNumResidents2", selected.features)]) ... ... @@ -183,5 +186,10 @@ auc_mean #the ROC curve shows true-positive-rate vs. false-positive rate plot(performance(pred, "tpr", "fpr")) # Test if the AUCs are expexted to be greater than random (AUC=0.5) t.test(auc_array, mu = 0.5, alternative = "greater") ```
 ... ... @@ -130,12 +130,15 @@ propabilities <- attributes(clres)\$probabilities ```{r Classification with an advanced evaluation technique: cross-validation} set.seed(1506) all_data\$crossfolds <- sample(1:5, nrow(all_data), replace = TRUE) folds <- 10 all_data\$crossfolds <- sample(1:folds, nrow(all_data), replace = TRUE) # list for the interim results results <- list() for(foldIndex in 1:5){ for(foldIndex in 1:folds){ # creating data for the testdata <- na.omit(all_data[all_data\$crossfolds==foldIndex, c("pNumResidents2", selected.features)]) traindata <- na.omit(all_data[all_data\$crossfolds!=foldIndex, c("pNumResidents2", selected.features)]) ... ...
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