40 citations · 83 across the 6 of their papers we have counts for
6 papers
Separate and conquer heuristic allows robust mining of contrast sets in classification, regression, and survival data
Adam Gudyś, Marek Sikora, Łukasz Wróbel
Identifying differences between groups is one of the most important knowledge discovery problems. The procedure, also known as contrast sets mining, is applied in a wide range of a…
SCARI: Separate and Conquer Algorithm for Action Rules and Recommendations Induction
Marek Sikora, Paweł Matyszok, Łukasz Wróbel
This article describes an action rule induction algorithm based on a sequential covering approach. Two variants of the algorithm are presented. The algorithm allows the action rule…
Classification supporting COVID-19 diagnostics based on patient survey data
Joanna Henzel, Joanna Tobiasz, Michał Kozielski +11
Distinguishing COVID-19 from other flu-like illnesses can be difficult due to ambiguous symptoms and still an initial experience of doctors. Whereas, it is crucial to filter out th…
Gradient Boosting Application in Forecasting of Performance Indicators Values for Measuring the Efficiency of Promotions in FMCG Retail
Joanna Henzel, Marek Sikora
In the paper, a problem of forecasting promotion efficiency is raised. The authors propose a new approach, using the gradient boosting method for this task. Six performance indicat…
RuleKit: A Comprehensive Suite for Rule-Based Learning
Adam Gudyś, Marek Sikora, Łukasz Wróbel
Rule-based models are often used for data analysis as they combine interpretability with predictive power. We present RuleKit, a versatile tool for rule learning. Based on a sequen…
GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settings
Marek Sikora, Łukasz Wróbel, Adam Gudyś
This article presents GuideR, a user-guided rule induction algorithm, which overcomes the largest limitation of the existing methods-the lack of the possibility to introduce user's…