train.cade: CADE
In Prometheus77/rcade:
Description
R implementation of Classifier-Adjusted Density Estimation, as
described by Friedland, Gentzel, and Jensen in their white paper "Classifier-Adjusted
Density Estimation for Anomaly Detection and One-Class Classification"
Usage
1
2
train.cade(df, classifier = "randomForest",
density.estimate = "uniform", true.prop = 0.5)
Arguments
df
data frame used for training
classifier
classifier used to distinguish between true and false data points, must be one of:
'randomForest'
'KNN'
'logistic'
'rpart'
'nb'
density.estimate
method used to create false data points, must be one of
'uniform'
'Gaussian'
'KDE'
true.prop
proportion of true data points in final training set
Prometheus77/rcade documentation built on Oct. 30, 2019, 10:44 p.m.
R Package Documentation
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Description
R implementation of Classifier-Adjusted Density Estimation, as described by Friedland, Gentzel, and Jensen in their white paper "Classifier-Adjusted Density Estimation for Anomaly Detection and One-Class Classification"
Usage
1 2 | train.cade(df, classifier = "randomForest",
density.estimate = "uniform", true.prop = 0.5)
|
Arguments
df |
data frame used for training |
classifier |
classifier used to distinguish between true and false data points, must be one of:
|
density.estimate |
method used to create false data points, must be one of
|
true.prop |
proportion of true data points in final training set |
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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