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bnnSurvival (version 0.1.5)

Bagged k-Nearest Neighbors Survival Prediction

Description

Implements a bootstrap aggregated (bagged) version of the k-nearest neighbors survival probability prediction method (Lowsky et al. 2013). In addition to the bootstrapping of training samples, the features can be subsampled in each baselearner to break the correlation between them. The Rcpp package is used to speed up the computation.

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Version

Install

install.packages('bnnSurvival')

Monthly Downloads

202

Version

0.1.5

License

GPL-3

Maintainer

Marvin Wright

Last Published

May 10th, 2017

Functions in bnnSurvival (0.1.5)

bnnSurvival

Bagged k-nearest neighbors survival prediction
get_best_k

Get optimal number of neighbors
print,bnnSurvivalResult-method

Generic print method for bnnSurvivalResult
show,bnnSurvivalEnsemble-method

Generic show method for bnnSurvivalEnsemble
predictions

Get Predictions
print,bnnSurvivalEnsemble-method

Generic print method for bnnSurvivalEnsemble
predictSurvProb.bnnSurvivalEnsemble

Function to extract survival probability predictions from bnnSurvivalEnsemble. Use with
predictions,bnnSurvivalResult-method

Get Predictions
timepoints

Get Timepoints
predict,bnnSurvivalBaseLearner-method

Compute prediction for all samples.
predict,bnnSurvivalEnsemble-method

Predict survival probabilities with bagged k-nearest neighbors survival prediction.
show,bnnSurvivalResult-method

Generic show method for bnnSurvivalResult
timepoints,bnnSurvivalResult-method

Get timepoints