diff --git a/pkgdown.yml b/pkgdown.yml index 40f0bce..0d28849 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -5,5 +5,5 @@ articles: BuildingDeepModels: BuildingDeepModels.html FirstModel: FirstModel.html Installing: Installing.html -last_built: 2023-09-07T08:19Z +last_built: 2023-09-07T15:12Z diff --git a/reference/checkHigher.html b/reference/checkHigher.html new file mode 100644 index 0000000..cabb940 --- /dev/null +++ b/reference/checkHigher.html @@ -0,0 +1,124 @@ + +
R/HelperFunctions.R
+ checkHigher.Rd
helper function to check that input is higher than a certain value
+checkHigher(parameter, value)
the input parameter to check, can be a vector
which value it should be higher than
R/HelperFunctions.R
+ checkHigherEqual.Rd
helper function to check that input is higher or equal than a certain value
+checkHigherEqual(parameter, value)
the input parameter to check, can be a vector
which value it should be higher or equal than
helper function to check class of input
+checkIsClass(parameter, classes)
the input parameter to check
which classes it should belong to (one or more)
camelCaseToSnakeCaseNames()
Convert the names of an object from camel case to snake case
helper function to check that input is higher than a certain value
helper function to check that input is higher or equal than a certain value
helper function to check class of input
setDefaultResNet(
estimatorSettings = setEstimator(learningRate = "auto", weightDecay = 1e-06, device =
- "cpu", batchSize = 1024L, epochs = 50L, seed = NULL)
+ "cpu", batchSize = 1024, epochs = 50, seed = NULL)
)
setDefaultTransformer(
estimatorSettings = setEstimator(learningRate = "auto", weightDecay = 1e-04, batchSize
- = 512L, epochs = 10L, seed = NULL, device = "cpu")
+ = 512, epochs = 10, seed = NULL, device = "cpu")
)
setEstimator(
learningRate = "auto",
weightDecay = 0,
- batchSize = 512L,
- epochs = 30L,
+ batchSize = 512,
+ epochs = 30,
device = "cpu",
optimizer = torch$optim$AdamW,
scheduler = list(fun = torch$optim$lr_scheduler$ReduceLROnPlateau, params =
- list(patience = 1L)),
+ list(patience = 1)),
criterion = torch$nn$BCEWithLogitsLoss,
- earlyStopping = list(useEarlyStopping = TRUE, params = list(patience = 4L)),
+ earlyStopping = list(useEarlyStopping = TRUE, params = list(patience = 4)),
metric = "auc",
seed = NULL
)
setMultiLayerPerceptron(
- numLayers = as.integer(1:8),
- sizeHidden = as.integer(2^(6:9)),
+ numLayers = c(1:8),
+ sizeHidden = c(2^(6:9)),
dropout = c(seq(0, 0.3, 0.05)),
- sizeEmbedding = as.integer(2^(6:9)),
+ sizeEmbedding = c(2^(6:9)),
estimatorSettings = setEstimator(learningRate = "auto", weightDecay = c(1e-06, 0.001),
- batchSize = 1024L, epochs = 30L, device = "cpu"),
+ batchSize = 1024, epochs = 30, device = "cpu"),
hyperParamSearch = "random",
randomSample = 100,
randomSampleSeed = NULL
diff --git a/reference/setResNet.html b/reference/setResNet.html
index 3bf8e11..6988735 100644
--- a/reference/setResNet.html
+++ b/reference/setResNet.html
@@ -85,14 +85,14 @@ setResNet
setResNet(
- numLayers = as.integer(1:8),
- sizeHidden = as.integer(2^(6:10)),
- hiddenFactor = as.integer(1:4),
+ numLayers = c(1:8),
+ sizeHidden = c(2^(6:10)),
+ hiddenFactor = c(1:4),
residualDropout = c(seq(0, 0.5, 0.05)),
hiddenDropout = c(seq(0, 0.5, 0.05)),
- sizeEmbedding = as.integer(2^(6:9)),
+ sizeEmbedding = c(2^(6:9)),
estimatorSettings = setEstimator(learningRate = "auto", weightDecay = c(1e-06, 0.001),
- device = "cpu", batchSize = 1024L, epochs = 30L, seed = NULL),
+ device = "cpu", batchSize = 1024, epochs = 30, seed = NULL),
hyperParamSearch = "random",
randomSample = 100,
randomSampleSeed = NULL
diff --git a/sitemap.xml b/sitemap.xml
index 8f4b3a6..4f7c24f 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -36,6 +36,15 @@
/reference/camelCaseToSnakeCaseNames.html
+
+ /reference/checkHigher.html
+
+
+ /reference/checkHigherEqual.html
+
+
+ /reference/checkIsClass.html
+
/reference/fitEstimator.html