Source code, sample data, and case study report for pyDRMetrics

Published: 8 February 2021| Version 2 | DOI: 10.17632/jbjd5fmggh.2
Contributor:
Yinsheng Zhang

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Supplemental Materials for the article "pyDRMetrics - A Python Toolkit for Dimensionality Reduction Quality Assessment" File list: src/pyDRMetrics.py - the main module src/other py files - dependent modules data/ovarian-cancer-nci-pbsii-data-no-header.csv - SELDI-TOF-MS dataset used in the case stduy. 253 samples. Each sample has 15154 dimensions. data/cancer.csv - A subset of ovarian-cancer-nci-pbsii-data containing 10 normal and 10 cancer samples. DOI: 10.1016/S0140-6736(02)07746-2 data/digits.csv - 40 samples from the MNIST handwritten digits dataset. URL: http://yann.lecun.com/exdb/mnist/ data/raman.csv - Another dataset containing the Raman spectra of 46 infant formula milk powder samples. DOI: 10.1016/j.talanta.2019.120681 notebook.pdf - the code and result for the case study Please Cite: pyDRMetrics - A Python toolkit for dimensionality reduction quality assessment, Heliyon, Volume 7, Issue 2, 2021, e06199, ISSN 2405-8440, https://doi.org/10.1016/j.heliyon.2021.e06199. (https://www.sciencedirect.com/science/article/pii/S2405844021003042)

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Dimensionality Reduction

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