Internal - Learn single random forest classifier

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Description

Internal function to learn a random forest classifier

Usage

1
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reptile_train_one_mode(epimark, label,
                       family, ntree, nodesize)

Arguments

epimark

data.frame instance from read_epigenomic_data, which containing intensity and intensity deviation values of each mark for each DMR or query region.

label

factor instance from read_label, containing the label of each query region. The possible values and their meanings of a label are: 0 (not enhancer), 1 (enhancer) and NA (unknwon and will be ignored).

family

Classifier family used in the enhancer model Default: RandomForest Classifiers available: - RandomForest: random forest - Logistic: logistic regression

ntree

Number of tree to be constructed in the random forest model. See the function randomForest() in "randomForest" package for more information. Default: 2000

nodesize

Minimum size of terminal nodes. See the function randomForest() in "randomForest" package for more information. Default: 1

Value

An randomForest object or glm object when family is set to be "Logistic".

Author(s)

Yupeng He yupeng.he.bioinfo@gmail.com

References

Breiman, L. (2001), Random Forests, Machine Learning 45(1), 5-32.

A. Liaw and M. Wiener (2002), Classification and Regression by randomForest, R News 2(3), 18–22.

See Also

reptile_train