bayesCaret: Provides a caret-compatible wrapper around functionality for...
In mmb: Arbitrary Dependency Mixed Multivariate Bayesian Models
Description
Usage
Format
Author(s)
Examples
Description
A wrapper to be used with the package/function caret::train().
Supports regression and classification and an extensive default grid.
Usage
1
Format
An object of class list of length 7.
Author(s)
Sebastian Hönel sebastian.honel@lnu.se
Examples
1
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11
trainIndex <- caret::createDataPartition(
iris$Species, p = .8, list = FALSE, times = 1)
train <- iris[ trainIndex, ]
test <- iris[-trainIndex, ]
fitControl <- caret::trainControl(
method = "repeatedcv", number = 2, repeats = 2)
fit <- caret::train(
Species ~ ., data = train, method = mmb::bayesCaret,
trControl = fitControl)
mmb documentation built on Oct. 23, 2020, 5:21 p.m.
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Description Usage Format Author(s) Examples
Description
A wrapper to be used with the package/function caret::train().
Supports regression and classification and an extensive default grid.
Usage
1 |
Format
An object of class list of length 7.
Author(s)
Sebastian Hönel sebastian.honel@lnu.se
Examples
1 2 3 4 5 6 7 8 9 10 11 | trainIndex <- caret::createDataPartition(
iris$Species, p = .8, list = FALSE, times = 1)
train <- iris[ trainIndex, ]
test <- iris[-trainIndex, ]
fitControl <- caret::trainControl(
method = "repeatedcv", number = 2, repeats = 2)
fit <- caret::train(
Species ~ ., data = train, method = mmb::bayesCaret,
trControl = fitControl)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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