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20172025
most citedWeighting Scheme for a Pairwise Multi-label Classifier Based on the Fuzzy Confusion Matrix

26 citations · 65 across the 13 of their papers we have counts for

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12 papers · 1 filter

cs.LG2025★ 6 cited

Application of Context-dependent Interpretation of Biosignals Recognition to Control a Bionic Multifunctional Hand Prosthesis

Pawel Trajdos, Marek Kurzynski

The paper presents an original method for controlling a surface-electromyography-driven (sEMG) prosthesis. A context-dependent recognition system is proposed in which the same clas…

cs.LG2024★ 1 cited

A dual ensemble classifier used to recognise contaminated multi-channel EMG and MMG signals in the control of upper limb bioprosthesis

Pawel Trajdos, Marek Kurzynski

Myopotential pattern recognition to decode the intent of the user is the most advanced approach to controlling a powered bioprosthesis. Unfortunately, many factors make this a diff…

cs.LG2021

Building an Ensemble of Classifiers via Randomized Models of Ensemble Members

Pawel Trajdos, Marek Kurzynski

Many dynamic ensemble selection (DES) methods are known in the literature. A previously-developed by the authors, method consists in building a randomized classifier which is treat…

cs.LG2021

Soft Confusion Matrix Classifier for Stream Classification

Pawel Trajdos, Marek Kurzynski

In this paper, the issue of tailoring the soft confusion matrix (SCM) based classifier to deal with stream learning task is addressed. The main goal of the work is to develop a wra…

cs.LG2021

Probability-driven scoring functions in combining linear classifiers

Pawel Trajdos, Robert Burduk

Although linear classifiers are one of the oldest methods in machine learning, they are still very popular in the machine learning community. This is due to their low computational…

cs.LG2020★ 6 cited

Linear Classifier Combination via Multiple Potential Functions

Pawel Trajdos, Robert Burduk

A vital aspect of the classification based model construction process is the calibration of the scoring function. One of the weaknesses of the calibration process is that it does n…

cs.LG2019★ 1 cited

Randomized Reference Classifier with Gaussian Distribution and Soft Confusion Matrix Applied to the Improving Weak Classifiers

Pawel Trajdos, Marek Kurzynski

In this paper, an issue of building the RRC model using probability distributions other than beta distribution is addressed. More precisely, in this paper, we propose to build the…

cs.LG2019★ 7 cited

Combination of linear classifiers using score function -- analysis of possible combination strategies

Pawel Trajdos, Robert Burduk

In this work, we addressed the issue of combining linear classifiers using their score functions. The value of the scoring function depends on the distance from the decision bounda…

cs.LG2019★ 1 cited

Bayes metaclassifier and Soft-confusion-matrix classifier in the task of multi-label classification

Pawel Trajdos, Marcin Majak

The aim of this paper was to compare soft confusion matrix approach and Bayes metaclassifier under the multi-label classification framework. Although the methods were successfully…

cs.LG2017★ 7 cited

Dynamic classifier chains for multi-label learning

Pawel Trajdos, Marek Kurzynski

In this paper, we deal with the task of building a dynamic ensemble of chain classifiers for multi-label classification. To do so, we proposed two concepts of classifier chains alg…

cs.LG2017★ 10 cited

A Correction Method of a Binary Classifier Applied to Multi-label Pairwise Models

Pawel Trajdos, Marek Kurzynski

In this work, we addressed the issue of applying a stochastic classifier and a local, fuzzy confusion matrix under the framework of multi-label classification. We proposed a novel…

cs.LG2017★ 26 cited

Weighting Scheme for a Pairwise Multi-label Classifier Based on the Fuzzy Confusion Matrix

Pawel Trajdos, Marek Kurzynski

In this work we addressed the issue of applying a stochastic classifier and a local, fuzzy confusion matrix under the framework of multi-label classification. We proposed a novel s…