26 citations · 65 across the 13 of their papers we have counts for
14 papers
A Compound Classification System Based on Fuzzy Relations Applied to the Noise-Tolerant Control of a Bionic Hand via EMG Signal Recognition
Pawel Trajdos, Marek Kurzynski
Modern anthropomorphic upper limb bioprostheses are typically controlled by electromyographic (EMG) biosignals using a pattern recognition scheme. Unfortunately, there are many fac…
Cascade of one-class classifier ensemble and dynamic naive Bayes classifier applied to the myoelectric-based upper limb prosthesis control with contaminated channels detection
Pawel Trajdos, Marek Kurzynski
Modern upper limb bioprostheses are typically controlled by sEMG signals using a pattern recognition scheme in the control process. Unfortunately, the sEMG signal is very susceptib…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…