Contact
A Bayesian Classifier that Learns the Task Complexity
Data scientist in Basel
2940
post-template-default,single,single-post,postid-2940,single-format-standard,bridge-core-3.1.8,qode-page-transition-enabled,ajax_fade,page_not_loaded,,qode_grid_1300,side_area_uncovered_from_content,overlapping_content,qode-content-sidebar-responsive,qode-theme-ver-30.5,qode-theme-bridge,disabled_footer_top,disabled_footer_bottom,qode_header_in_grid,wpb-js-composer js-comp-ver-7.6,vc_responsive

A Bayesian Classifier that Learns the Task Complexity

15 Aug A Bayesian Classifier that Learns the Task Complexity

Posted at 07:16h in Data Science by

Robust machine-learning classification with adequate simplicity by determining the structure of the task.

Classification

Classification is a challenge for AI and humans alike. I’ve created a new classifier that can adapt the so-called Naïve Bayes, which is a key assumption of a robust Bayesian classification algorithm. The new classifier can learn if the data seems to violate the assumption, and adjust classification accordingly.

Realization

Design in R-Statistics, JavaScript, PhP. Part of the Deutsche Forschungsgemeinschaft (DFG) priority program New Frameworks of Rationality.

Read More

You can read the scientific paper in Cognitive Science.

Print page