bnnSurvival0.1.5 package

Bagged k-Nearest Neighbors Survival Prediction

bnnSurvival

Bagged k-nearest neighbors survival prediction

get_best_k

Get optimal number of neighbors

predict-bnnSurvivalBaseLearner-method

Compute prediction for all samples.

predict-bnnSurvivalEnsemble-method

Predict survival probabilities with bagged k-nearest neighbors surviva...

predictions-bnnSurvivalResult-method

Get Predictions

predictions

Get Predictions

predictSurvProb.bnnSurvivalEnsemble

Function to extract survival probability predictions from bnnSurvivalE...

print-bnnSurvivalEnsemble-method

Generic print method for bnnSurvivalEnsemble

print-bnnSurvivalResult-method

Generic print method for bnnSurvivalResult

show-bnnSurvivalEnsemble-method

Generic show method for bnnSurvivalEnsemble

show-bnnSurvivalResult-method

Generic show method for bnnSurvivalResult

timepoints-bnnSurvivalResult-method

Get timepoints

timepoints

Get Timepoints

Download source packageRead PDF manual

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.

  • Maintainer: Marvin N. Wright
  • License: GPL-3
  • Last published: 2017-05-10