trainClass


This is an adapted leukemia (ALL, AML) dataset from Golub et al. (1999).
This is a zero-one vector for 38 training samples.  Class 0 represents
an ALL sample, while class 1 represents an AML sample.


datasets

The iterative Bayesian Model Averaging (BMA) algorithm is
a variable selection and classification algorithm with an
application of classifying 2-class microarray samples, as
described in Yeung, Bumgarner and Raftery (Bioinformatics 2005,
21: 2394-2402).

Ka Yeung

iterativeBMA

The Iterative Bayesian Model Averaging (BMA) algorithm

trainClass function

The vector is called <code>trainClass</code>.

Format

The <code>golubEsets</code> bioconductor data package, or
<a href="http://www.broad.mit.edu/cgi-bin/cancer/datasets.cgi">http://www.broad.mit.edu/cgi-bin/cancer/datasets.cgi</a>.

Source

This is an adapted leukemia (ALL, AML) dataset from Golub et al. (1999).
This is a zero-one vector for 38 training samples.  Class 0 represents
an ALL sample, while class 1 represents an AML sample.

trainClass: Sample Training Data for the Iterative BMA Algorithm

Description

Usage

Arguments

Format

Source

Details

References