neuroblastomaProcessed: Processed neuroblastoma data set with features and targets

In tdhock/penaltyLearning: Penalty Learning

Processed neuroblastoma data set with features and targets

Description

Features are inputs and targets are outputs for penalty learning functions like penaltyLearning::IntervalRegressionCV. data(neuroblastoma, package="neuroblastoma") was processed by computing optimal Gaussian segmentation models from 1 to 20 segments (cghseg:::segmeanCO or Segmentor3IsBack::Segmentor), then label error was computed using neuroblastoma$annotations (penaltyLearning::labelError), then target intervals were computed (penaltyLearning::targetInterval). Features were also computed based on neuroblastoma$profiles.

Usage

data("neuroblastomaProcessed")

Format

List of two matrices: feature.mat is n.observations x n.features, and target.mat is n.observations x 2, where n.observations=3418 and n.features=117.

tdhock/penaltyLearning documentation built on Jan. 27, 2024, 9:02 p.m.