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stepwiseCM (version 1.18.0)

Stepwise Classification of Cancer Samples using High-dimensional Data Sets

Description

Stepwise classification of cancer samples using multiple data sets. This package implements the classification strategy using two heterogeneous data sets without actually combining them. Package uses the data type for which full measurements are available at the first stage, and the data type for which only partial measurements are available at the second stage. For incoming new samples package quantifies how much improvement will be obtained if covariates of new samples for the data types at the second stage are measured. This packages suits for the application where study goal is not only obtain high classification accuracy, but also requires economically cheap classifier.

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Version

Version

1.18.0

License

GPL (>2)

Maintainer

Askar Obulkasim

Last Published

February 15th, 2017

Functions in stepwiseCM (1.18.0)

Curve.generator

A function to generate accuracy curve by passing different portion of samples to the data set used at the second stage.
Classifier.par

A function to perform classification task by multi-core computation.
Classifier

A function to perform classification task.
stepwiseCM-package

Stepwise classification of cancer samples using high-dimensional data sets.
RS.generator

A function to generate the reclassification score.
Proximity

A function to calculate the proximity matrix.
CNS

Central Nervous System (CNS) cancer data set.
Step.pred

A function to generate RS cutoff point based the given re-classification percentage.