{"id":9580,"date":"2026-01-08T07:02:28","date_gmt":"2026-01-08T07:02:28","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2026\/01\/08\/2601-04149\/"},"modified":"2026-01-08T07:02:28","modified_gmt":"2026-01-08T07:02:28","slug":"2601-04149","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2026\/01\/08\/2601-04149\/","title":{"rendered":"A Theoretical and Empirical Taxonomy of Imbalance in Binary Classification"},"content":{"rendered":"

A Theoretical and Empirical Taxonomy of Imbalance in Binary Classification
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arXiv:2601.04149v1 Announce Type: new
\nAbstract: Class imbalance significantly degrades classification performance, yet its effects are rarely analyzed from a unified theoretical perspective. We propose a principled framework based on three fundamental scales: the imbalance coefficient $eta$, the sample–dimension ratio $kappa$, and the intrinsic separability $Delta$. Starting from the Gaussian Bayes classifier, we derive closed-form Bayes errors and show how imbalance shifts the discriminant boundary, yielding a deterioration slope that predicts four regimes: Normal, Mild, Extreme, and Catastrophic. Using a balanced high-dimensional genomic dataset, we vary only $eta$ while keeping $kappa$ and $Delta$ fixed. Across parametric and non-parametric models, empirical degradation closely follows theoretical predictions: minority Recall collapses once $log(eta)$ exceeds $Deltasqrt{kappa}$, Precision increases asymmetrically, and F1-score and PR-AUC decline in line with the predicted regimes. These results show that the triplet $(eta,kappa,Delta)$ provides a model-agnostic, geometrically grounded explanation of imbalance-induced deterioration.<\/div>\n

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\n Rose Yvette Bandolo Essomba, Ernest Fokou’e
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A Theoretical and Empirical Taxonomy of Imbalance in Binary Classification arXiv:2601.04149v1 Announce Type: new Abstract: Class imbalance significantly degrades classification performance, yet its effects are rarely analyzed from a unified theoretical perspective. We propose a principled framework based on three fundamental scales: the imbalance coefficient $eta$, the sample–dimension ratio $kappa$, and the intrinsic separability $Delta$. […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,113,112],"tags":[4085,707,1628],"class_list":["post-9580","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-cs-lg","category-stat-ml","tag-eta","tag-imbalance","tag-theoretical"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/9580"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=9580"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/9580\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=9580"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=9580"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=9580"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}