53 citations · 139 across the 10 of their papers we have counts for
7 papers · 1 filter
Kendall transformation: a robust representation of continuous data for information theory
Miron Bartosz Kursa
Kendall transformation is a conversion of an ordered feature into a vector of pairwise order relations between individual values. This way, it preserves ranking of observations and…
Embedded all relevant feature selection with Random Ferns
Miron Bartosz Kursa
Many machine learning methods can produce variable importance scores expressing the usability of each feature in context of the produced model; those scores on their own are yet no…
Generalised Random Forest Space Overview
Miron B. Kursa
Assuming a view of the Random Forest as a special case of a nested ensemble of interchangeable modules, we construct a generalisation space allowing one to easily develop novel met…
Multi-label Ferns for Efficient Recognition of Musical Instruments in Recordings
Miron B. Kursa, Alicja A. Wieczorkowska
In this paper we introduce multi-label ferns, and apply this technique for automatic classification of musical instruments in audio recordings. We compare the performance of our pr…
A Comparison of Random Forests and Ferns on Recognition of Instruments in Jazz Recordings
Alicja A. Wieczorkowska, Miron B. Kursa
In this paper, we first apply random ferns for classification of real music recordings of a jazz band. No initial segmentation of audio data is assumed, i.e., no onset, offset, nor…
Robustness of Random Forest-based gene selection methods
Miron B. Kursa
Gene selection is an important part of microarray data analysis because it provides information that can lead to a better mechanistic understanding of an investigated phenomenon. A…