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Added a column name to the matrix
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@topepo
topepo committed Apr 12, 2017
1 parent e5ae884 commit bd85fb9
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Showing 3 changed files with 26 additions and 20 deletions.
14 changes: 8 additions & 6 deletions RegressionTests/Code/svmBoundrangeString.R
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,8 @@ model <- "svmBoundrangeString"

library(kernlab)
data(reuters)
reuters <- matrix(reuters, ncol = 1)
colnames(reuters) <- "text"

cctrl1 <- trainControl(method = "cv", number = 3, returnResamp = "all")
cctrl2 <- trainControl(method = "LOOCV", savePredictions = TRUE)
Expand All @@ -15,11 +17,11 @@ cctrl3 <- trainControl(method = "none",
cctrlR <- trainControl(method = "cv", number = 3, returnResamp = "all", search = "random")

set.seed(849)
test_class_cv_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_cv_model <- train(reuters, rlabels,
method = "svmBoundrangeString",
trControl = cctrl1)

test_class_pred <- predict(test_class_cv_model, matrix(reuters, ncol = 1))
test_class_pred <- predict(test_class_cv_model, reuters)

set.seed(849)
test_class_rand <- train(matrix(reuters, ncol = 1), rlabels,
Expand All @@ -28,19 +30,19 @@ test_class_rand <- train(matrix(reuters, ncol = 1), rlabels,
tuneLength = 4)

set.seed(849)
test_class_loo_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_loo_model <- train(reuters, rlabels,
method = "svmBoundrangeString",
trControl = cctrl2)

set.seed(849)
test_class_none_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_none_model <- train(reuters, rlabels,
method = "svmBoundrangeString",
trControl = cctrl3,
tuneGrid = test_class_cv_model$bestTune,
metric = "ROC")

test_class_none_pred <- predict(test_class_none_model, matrix(reuters, ncol = 1))
test_class_none_prob <- predict(test_class_none_model, matrix(reuters, ncol = 1), type = "prob")
test_class_none_pred <- predict(test_class_none_model, reuters)
test_class_none_prob <- predict(test_class_none_model, reuters, type = "prob")

test_levels <- levels(test_class_cv_model)
if(!all(levels(rlabels) %in% test_levels))
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16 changes: 9 additions & 7 deletions RegressionTests/Code/svmExpoString.R
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,8 @@ model <- "svmExpoString"

library(kernlab)
data(reuters)
reuters <- matrix(reuters, ncol = 1)
colnames(reuters) <- "text"

cctrl1 <- trainControl(method = "cv", number = 3, returnResamp = "all")
cctrl2 <- trainControl(method = "LOOCV", savePredictions = TRUE)
Expand All @@ -15,34 +17,34 @@ cctrl3 <- trainControl(method = "none",
cctrlR <- trainControl(method = "cv", number = 3, returnResamp = "all", search = "random")

set.seed(849)
test_class_cv_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_cv_model <- train(reuters, rlabels,
method = "svmExpoString",
tuneLength = 2,
trControl = cctrl1)

test_class_pred <- predict(test_class_cv_model, matrix(reuters, ncol = 1))
test_class_pred <- predict(test_class_cv_model, reuters)

set.seed(849)
test_class_rand <- train(matrix(reuters, ncol = 1), rlabels,
test_class_rand <- train(reuters, rlabels,
method = "svmExpoString",
trControl = cctrlR,
tuneLength = 4)

set.seed(849)
test_class_loo_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_loo_model <- train(reuters, rlabels,
method = "svmExpoString",
tuneLength = 2,
trControl = cctrl2)

set.seed(849)
test_class_none_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_none_model <- train(reuters, rlabels,
method = "svmExpoString",
trControl = cctrl3,
tuneGrid = test_class_cv_model$bestTune,
metric = "ROC")

test_class_none_pred <- predict(test_class_none_model, matrix(reuters, ncol = 1))
test_class_none_prob <- predict(test_class_none_model, matrix(reuters, ncol = 1), type = "prob")
test_class_none_pred <- predict(test_class_none_model, reuters)
test_class_none_prob <- predict(test_class_none_model, reuters, type = "prob")

test_levels <- levels(test_class_cv_model)
if(!all(levels(rlabels) %in% test_levels))
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16 changes: 9 additions & 7 deletions RegressionTests/Code/svmSpectrumString.R
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,8 @@ model <- "svmSpectrumString"

library(kernlab)
data(reuters)
reuters <- matrix(reuters, ncol = 1)
colnames(reuters) <- "text"

cctrl1 <- trainControl(method = "cv", number = 3, returnResamp = "all")
cctrl2 <- trainControl(method = "LOOCV", savePredictions = TRUE)
Expand All @@ -15,32 +17,32 @@ cctrl3 <- trainControl(method = "none",
cctrlR <- trainControl(method = "cv", number = 3, returnResamp = "all", search = "random")

set.seed(849)
test_class_cv_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_cv_model <- train(reuters, rlabels,
method = "svmSpectrumString",
trControl = cctrl1)

test_class_pred <- predict(test_class_cv_model, matrix(reuters, ncol = 1))
test_class_pred <- predict(test_class_cv_model, reuters)

set.seed(849)
test_class_rand <- train(matrix(reuters, ncol = 1), rlabels,
test_class_rand <- train(reuters, rlabels,
method = "svmSpectrumString",
trControl = cctrlR,
tuneLength = 4)

set.seed(849)
test_class_loo_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_loo_model <- train(reuters, rlabels,
method = "svmSpectrumString",
trControl = cctrl2)

set.seed(849)
test_class_none_model <- train(matrix(reuters, ncol = 1), rlabels,
test_class_none_model <- train(reuters, rlabels,
method = "svmSpectrumString",
trControl = cctrl3,
tuneGrid = test_class_cv_model$bestTune,
metric = "ROC")

test_class_none_pred <- predict(test_class_none_model, matrix(reuters, ncol = 1))
test_class_none_prob <- predict(test_class_none_model, matrix(reuters, ncol = 1), type = "prob")
test_class_none_pred <- predict(test_class_none_model, reuters)
test_class_none_prob <- predict(test_class_none_model, reuters, type = "prob")

test_levels <- levels(test_class_cv_model)
if(!all(levels(rlabels) %in% test_levels))
Expand Down

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