From 6aae0713df5ff23a181675e23d6bcf8be9d3f9c5 Mon Sep 17 00:00:00 2001 From: lucaurelien <133773992+lucaurelien@users.noreply.github.com> Date: Wed, 22 Jan 2025 14:54:44 +0100 Subject: [PATCH] Update bibliography with new SNB reference #62 --- docs/references.md | 15 +++++---------- 1 file changed, 5 insertions(+), 10 deletions(-) diff --git a/docs/references.md b/docs/references.md index 56da5a3..86625a5 100644 --- a/docs/references.md +++ b/docs/references.md @@ -3,17 +3,12 @@ hide: toc --- # Bibliography { #publications } +!!! note "More than a hundred articles about Khiops are available [on this page:octicons-link-external-16:][home_page_marc]{:target="_blank"}. " + To go further, here's a selection of **scientific papers** organized according to a reading path which facilitates the understanding of the Auto-ML pipeline. It is highly recommended to read these papers in the suggested order, after reading the documentation presented on this website. The **gray** lines indicate additional information, which can be read at a later stage, and which will not prevent you from gaining an overall understanding of the pipeline. [home_page_marc]: http://www.marc-boulle.fr/author/Marc.Boulle-eng.html - - - auto-ml-pipeline - - -!!! note "More than a hundred articles about Khiops are available [on this page:octicons-link-external-16:][home_page_marc]{:target="_blank"}. " - ## Optimal Encoding 1. **Discretization models:** MODL: a Bayes optimal discretization method for continuous attributes - [download:octicons-link-external-16:][paper_discretization]{:target="_blank"} @@ -36,8 +31,8 @@ To go further, here's a selection of **scientific papers** organized according t ## Parsimonious Training -1. **Previous versions:** Compression-Based Averaging of Selective Naive Bayes Classifiers - [download:octicons-link-external-16:][paper_snb]{:target="_blank"} -2. **Currently, from Khiops V10:** *an article is currently being written on the parsimonious Bayesian classifier as presented in the documentation.* +1. **Fractional Naive Bayes (FNB):** Non-convex optimization for a parsimonious weighted selective naive Bayes classifier - [download:octicons-link-external-16:][paper_fnb]{:target="_blank"} +2. **Previous versions (Khiops