diff --git a/dev/pkgdown.yml b/dev/pkgdown.yml index 380d84aa..b8c301bb 100644 --- a/dev/pkgdown.yml +++ b/dev/pkgdown.yml @@ -16,4 +16,4 @@ articles: CreatingNetworkStudies: CreatingNetworkStudies.html InstallationGuide: InstallationGuide.html Videos: Videos.html -last_built: 2024-12-10T13:44Z +last_built: 2024-12-10T13:52Z diff --git a/dev/reference/createDefaultSplitSetting.html b/dev/reference/createDefaultSplitSetting.html index 4b42d41b..794e8381 100644 --- a/dev/reference/createDefaultSplitSetting.html +++ b/dev/reference/createDefaultSplitSetting.html @@ -139,7 +139,7 @@

Create the settings for defining how the plpData are split into test/validat 
createDefaultSplitSetting(
   testFraction = 0.25,
   trainFraction = 0.75,
-  splitSeed = sample(100000, 1),
+  splitSeed = sample(1e+05, 1),
   nfold = 3,
   type = "stratified"
 )
diff --git a/dev/reference/setAdaBoost.html b/dev/reference/setAdaBoost.html index b11dd191..ca9a77aa 100644 --- a/dev/reference/setAdaBoost.html +++ b/dev/reference/setAdaBoost.html @@ -136,7 +136,7 @@

Create setting for AdaBoost with python DecisionTreeClassifier base estimato nEstimators = list(10, 50, 200), learningRate = list(1, 0.5, 0.1), algorithm = list("SAMME"), - seed = sample(1000000, 1) + seed = sample(1e+06, 1) ) diff --git a/dev/reference/setCoxModel.html b/dev/reference/setCoxModel.html index a099b5da..b08d636d 100644 --- a/dev/reference/setCoxModel.html +++ b/dev/reference/setCoxModel.html @@ -140,7 +140,7 @@

Create setting for lasso Cox model

threads = -1, upperLimit = 20, lowerLimit = 0.01, - tolerance = 0.0000002, + tolerance = 2e-07, maxIterations = 3000 ) diff --git a/dev/reference/setDecisionTree.html b/dev/reference/setDecisionTree.html index eb804695..9e9423a6 100644 --- a/dev/reference/setDecisionTree.html +++ b/dev/reference/setDecisionTree.html @@ -143,7 +143,7 @@

Create setting for the scikit-learn DecisionTree with python

maxLeafNodes = list(NULL), minImpurityDecrease = list(10^-7), classWeight = list(NULL), - seed = sample(1000000, 1) + seed = sample(1e+06, 1) ) diff --git a/dev/reference/setGradientBoostingMachine.html b/dev/reference/setGradientBoostingMachine.html index 41810b24..32328757 100644 --- a/dev/reference/setGradientBoostingMachine.html +++ b/dev/reference/setGradientBoostingMachine.html @@ -142,7 +142,7 @@

Create setting for gradient boosting machine model using gbm_xgboost impleme scalePosWeight = 1, lambda = 1, alpha = 0, - seed = sample(10000000, 1) + seed = sample(1e+07, 1) ) diff --git a/dev/reference/setIterativeHardThresholding.html b/dev/reference/setIterativeHardThresholding.html index 9965668d..fb20316d 100644 --- a/dev/reference/setIterativeHardThresholding.html +++ b/dev/reference/setIterativeHardThresholding.html @@ -135,14 +135,14 @@

Create setting for lasso logistic regression

setIterativeHardThresholding(
   K = 10,
   penalty = "bic",
-  seed = sample(100000, 1),
+  seed = sample(1e+05, 1),
   exclude = c(),
-  forceIntercept = F,
+  forceIntercept = FALSE,
   fitBestSubset = FALSE,
-  initialRidgeVariance = 10000,
-  tolerance = 0.00000001,
+  initialRidgeVariance = 0.1,
+  tolerance = 1e-08,
   maxIterations = 10000,
-  threshold = 0.000001,
+  threshold = 1e-06,
   delta = 0
 )
diff --git a/dev/reference/setLassoLogisticRegression.html b/dev/reference/setLassoLogisticRegression.html index 34d55482..0c70791e 100644 --- a/dev/reference/setLassoLogisticRegression.html +++ b/dev/reference/setLassoLogisticRegression.html @@ -141,7 +141,7 @@

Create setting for lasso logistic regression

forceIntercept = F, upperLimit = 20, lowerLimit = 0.01, - tolerance = 0.000002, + tolerance = 2e-06, maxIterations = 3000, priorCoefs = NULL ) diff --git a/dev/reference/setLightGBM.html b/dev/reference/setLightGBM.html index 1fd38f75..bce7344e 100644 --- a/dev/reference/setLightGBM.html +++ b/dev/reference/setLightGBM.html @@ -144,7 +144,7 @@

Create setting for gradient boosting machine model using lightGBM (https://g lambdaL2 = c(0), scalePosWeight = 1, isUnbalance = FALSE, - seed = sample(10000000, 1) + seed = sample(1e+07, 1) ) diff --git a/dev/reference/setMLP.html b/dev/reference/setMLP.html index 72eb4006..0c3cae34 100644 --- a/dev/reference/setMLP.html +++ b/dev/reference/setMLP.html @@ -136,14 +136,14 @@

Create setting for neural network model with python

hiddenLayerSizes = list(c(100), c(20)), activation = list("relu"), solver = list("adam"), - alpha = list(0.3, 0.01, 0.0001, 0.000001), + alpha = list(0.3, 0.01, 1e-04, 1e-06), batchSize = list("auto"), learningRate = list("constant"), learningRateInit = list(0.001), powerT = list(0.5), maxIter = list(200, 100), shuffle = list(TRUE), - tol = list(0.0001), + tol = list(1e-04), warmStart = list(TRUE), momentum = list(0.9), nesterovsMomentum = list(TRUE), @@ -151,9 +151,9 @@

Create setting for neural network model with python

validationFraction = list(0.1), beta1 = list(0.9), beta2 = list(0.999), - epsilon = list(0.00000001), + epsilon = list(1e-08), nIterNoChange = list(10), - seed = sample(100000, 1) + seed = sample(1e+05, 1) ) diff --git a/dev/reference/setRandomForest.html b/dev/reference/setRandomForest.html index 9afa3a3b..edc0e774 100644 --- a/dev/reference/setRandomForest.html +++ b/dev/reference/setRandomForest.html @@ -147,7 +147,7 @@

Create setting for random forest model with python (very fast)

oobScore = list(FALSE), nJobs = list(NULL), classWeight = list(NULL), - seed = sample(100000, 1) + seed = sample(1e+05, 1) ) diff --git a/dev/reference/setSVM.html b/dev/reference/setSVM.html index 26322602..cc9b5908 100644 --- a/dev/reference/setSVM.html +++ b/dev/reference/setSVM.html @@ -136,13 +136,13 @@

Create setting for the python sklearn SVM (SVC function)

C = list(1, 0.9, 2, 0.1), kernel = list("rbf"), degree = list(1, 3, 5), - gamma = list("scale", 0.0001, 0.00003, 0.001, 0.01, 0.25), + gamma = list("scale", 1e-04, 3e-05, 0.001, 0.01, 0.25), coef0 = list(0), shrinking = list(TRUE), tol = list(0.001), classWeight = list(NULL), cacheSize = 500, - seed = sample(100000, 1) + seed = sample(1e+05, 1) )