![Zdjęcie profilowe: Prof. Ireneusz Czarnowski](/assets/ireneusz-czarnowski,190307074040340-0/photo.png)
Prof. Ireneusz Czarnowski
Zatrudnienie
- Profesor UMG w Uniwersytet Morski w Gdyni
Publikacje
Filtry
wszystkich: 70
Katalog Publikacji
Rok 2022
-
Impact of Clustering on a Synthetic Instance Generation in Imbalanced Data Streams Classification
Publikacja -
Multi-Label Classification for AIS Data Anomaly Detection Using Wavelet Transform
Publikacja -
Using the AHP Method to Select an Electronic Documentation Management System for Polish Municipalities
Publikacja -
Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
Publikacja
Rok 2021
-
Designing RBFNs Structure Using Similarity-Based and Kernel-Based Fuzzy C-Means Clustering Algorithms
Publikacja -
Impact of the Time Window Length on the Ship Trajectory Reconstruction Based on AIS Data Clustering
Publikacja -
K-means clustering for SAT-AIS data analysis
Publikacja -
Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
Publikacja -
Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
Publikacja -
Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
Publikacja
Rok 2020
Rok 2019
-
An Approach to Imbalanced Data Classification Based on Instance Selection and Over-Sampling
Publikacja -
Data reduction and stacking for imbalanced data classification
Publikacja
Rok 2018
-
An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
Publikacja -
Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
Publikacja -
Stacking-Based Integrated Machine Learning with Data Reduction
Publikacja
Rok 2017
-
Learning from examples with data reduction and stacked generalization
Publikacja -
Preface
Publikacja -
Stacking and rotation-based technique for machine learning classification with data reduction
Publikacja
Rok 2016
-
Agent-Based RBF Network Classifier with Feature Selection in a Kernel Space
Publikacja -
An approach to machine classification based on stacked generalization and instance selection
Publikacja -
Bi-criteria Data Reduction for Instance-Based Classification
Publikacja -
Kernel-Based Fuzzy C-Means Clustering Algorithm for RBF Network Initialization
Publikacja
Rok 2015
-
An Approach to RBF Initialization with Feature Selection
Publikacja -
An Experimental Study of Scenarios for the Agent-Based RBF Network Design
Publikacja -
Cluster-Dependent Feature Selection for the RBF Networks
Publikacja -
Cluster-dependent rotation-based feature selection for the RBF networks initialization
Publikacja -
Ensemble Online Classifier Based on the One-Class Base Classifiers for Mining Data Streams
Publikacja -
Preface
Publikacja
Rok 2014
-
Designing RBF Networks Using the Agent-Based Population Learning Algorithm
Publikacja -
Ensemble Classifier for Mining Data Streams
Publikacja -
Online Learning Based on Prototypes
Publikacja -
Preface
Publikacja
Rok 2013
-
AGENT-BASED APPROACH TO THE DESIGN OF RBF NETWORKS
Publikacja -
Agent-Based Data Reduction Using Ensemble Technique
Publikacja -
Agent-Based Population Learning Algorithm for RBF Network Tuning
Publikacja -
Consensus-based cluster merging for the prototype selection
Publikacja
Rok 2012
-
Agent-Based Approach to RBF Network Training with Floating Centroids
Publikacja -
Cluster-based instance selection for machine classification
Publikacja -
SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
Publikacja
Rok 2011
-
A consensus-based approach to the distributed learning
Publikacja -
A New Cluster-based Instance Selection Algorithm
Publikacja -
An agent-based framework for distributed learning
Publikacja -
Application of agent-based simulated annealing and tabu search procedures to solving the data reduction problem
Publikacja -
Distributed Learning with Data Reduction
Publikacja -
Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
Publikacja -
Parallel Cooperating A-Teams
Publikacja -
POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
Publikacja
Rok 2010
wyświetlono 1381 razy