<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>maharaniau.r-universe.dev</title><link>https://maharaniau.r-universe.dev</link><description>Recent package updates in maharaniau</description><generator>R-universe</generator><image><url>https://github.com/maharaniau.png</url><title>R packages by maharaniau</title><link>https://maharaniau.r-universe.dev</link></image><lastBuildDate>Tue, 28 Apr 2026 13:07:13 GMT</lastBuildDate><item><title>[bioc] wavFeatExt 1.1.0</title><author>maharaniahsani@itb.ac.id (Maharani Ahsani Ummi)</author><description>Provides tools for simulating copy-number alteration (CNA)
profiles, applying a non-decimated Haar wavelet transform to
genomic signals, and extracting wavelet-derived features for
use in supervised learning. Multiple machine learning methods
including lasso and elastic-net regularisation, random forest,
partial least squares, neural networks and k-nearest neighbours
are implemented to train predictive models from genomic feature
vectors. The workflow enables end-to-end analysis from CNA
simulation to feature extraction and classification.</description><link>https://github.com/r-universe/bioc/actions/runs/38129802463</link><pubDate>Tue, 28 Apr 2026 13:07:13 GMT</pubDate><r:package>wavFeatExt</r:package><r:version>1.1.0</r:version><r:status>success</r:status><r:repository>https://bioc.r-universe.dev</r:repository><r:upstream>https://github.com/bioc/wavFeatExt</r:upstream><r:article><r:source>wavFeatExt.Rmd</r:source><r:filename>wavFeatExt.html</r:filename><r:title>wavFeatExt: Wavelet-based Feature Extraction for Copy-number Alteration Data</r:title><r:created>2026-04-02 08:10:17</r:created><r:modified>2026-04-20 02:59:22</r:modified></r:article></item></channel></rss>