Analysis of presence-only data via semi-supervised learning approaches

DOI10.1016/j.csda.2012.10.007zbMath1400.62137OpenAlexW1978419796MaRDI QIDQ1621212

Junhui Wang, Yixin Fang

Publication date: 8 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2012.10.007

zbMATH Keywords

stabilitytuningcross validationsupport vector machinefunctional genomics

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Dynamic Tensor Clustering

Uses Software

• NeNMF

Cites Work

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• Semi-supervised learning on Riemannian manifolds
• Consistent selection of the number of clusters via crossvalidation
• Probability estimation for large-margin classifiers
• Presence‐Only Data and the EM Algorithm
• NeNMF: An Optimal Gradient Method for Nonnegative Matrix Factorization
• Stability Selection
• Linear Model Selection by Cross-Validation
• Convergence of stochastic processes

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