Tomasz Ząbkowski

发表

Data Mining Techniques for Detecting Household Characteristics Based on Smart Meter Data

Krzysztof Gajowniczek, Tomasz Ząbkowski, T. Zabkowski, 2015 .

Badanie atrakcyjności oferty dostępu do internetu za pomocą analizy gradacyjnej

Tomasz Ząbkowski, Wiesław Szczesny, 2012 .

Analysis of Financial Time Series Morphology with AMUSE Algorithm and Its Extensions

Ryszard Szupiluk, Tomasz Ząbkowski, T. Sobon, 2016 .

Two-Stage Electricity Demand Modeling Using Machine Learning Algorithms

Krzysztof Gajowniczek, Tomasz Ząbkowski, T. Zabkowski, 2017 .

Zastosowanie sztucznych sieci neuronowych do oceny ryzyka kredytowego klienta w telekomunikacji

Tomasz Ząbkowski, 2008 .

Ensemble methods with non-negative matrix factorization for non-payment prevention system

Ryszard Szupiluk, Tomasz Ząbkowski, Piotr Wojewnik, 2007 .

Electricity forecasting on the individual household level enhanced based on activity patterns

Krzysztof Gajowniczek, Tomasz Ząbkowski, T. Zabkowski, 2017, PloS one.

ICA method and RBF neural network for prediction improvement

Krzysztof Siwek, Ryszard Szupiluk, Tomasz Ząbkowski, 2007 .

Simulation Study on the Electricity Data Streams Time Series Clustering

Chu Kiong Loo, Krzysztof Gajowniczek, Tomasz Ząbkowski, 2020, Energies.

SMART METERING – A BRIEF OVERVIEW OF PROJECTS, BENEFITS AND APPLICATIONS

Tomasz Ząbkowski, Arkadiusz Orłowski, Marcin Bator, 2012 .

Semantic and Generalized Entropy Loss Functions for Semi-Supervised Deep Learning

Guy Van den Broeck, Yitao Liang, Krzysztof Gajowniczek, 2020, Entropy.

Seasonal Peak Demand Classification with Machine Learning Techniques

Krzysztof Gajowniczek, Tomasz Ząbkowski, Rafik Nafkha, 2018, 2018 International Conference on Applied Mathematics & Computer Science (ICAMCS).

Problemy modelowania rezygnacji klientów w telefonii komórkowej

Krzysztof Gajowniczek, Tomasz Ząbkowski, 2012 .

Blind Source Separation for the Aggregation of Machine Learning Algorithms: An Arrhythmia Classification Case

Krzysztof Gajowniczek, Tomasz Ząbkowski, Iga Grzegorczyk, 2020, Electronics.

SMART METERING AND DATA PRIVACY ISSUES

Krzysztof Gajowniczek, Tomasz Ząbkowski, 2013 .

Insolvency modeling with generalized entropy cost function in neural networks

Krzysztof Gajowniczek, Tomasz Ząbkowski, Arkadiusz Orłowski, 2019, Physica A: Statistical Mechanics and its Applications.

Automated Computational Framework for Efficient Knowledge Utilization in Data Mining Process

Tomasz Ząbkowski, 2006 .

Weighted Random Forests to Improve Arrhythmia Classification

Krzysztof Gajowniczek, Tomasz Ząbkowski, Chandrajit Bajaj, 2020, Electronics.

Whole Time Series Data Streams Clustering: Dynamic Profiling of the Electricity Consumption

Krzysztof Gajowniczek, Tomasz Ząbkowski, Marcin Bator, 2020, Entropy.

Forecasting of Individual Electricity Usage Using Smart Meter Data

Krzysztof Gajowniczek, Tomasz Ząbkowski, T. Zabkowski, 2013 .

Do Customers Choose Proper Tariff? Empirical Analysis Based on Polish Data Using Unsupervised Techniques

Krzysztof Gajowniczek, Tomasz Ząbkowski, Rafik Nafkha, 2018 .

EGLD system for noise identification in ensemble predictors

Ryszard Szupiluk, Tomasz Ząbkowski, R. Szupiluk, 2014 .

Estimating the ROC Curve and Its Significance for Classification Models' Assessment

Ryszard Szupiluk, Krzysztof Gajowniczek, Tomasz Ząbkowski, 2014 .

Postprocessing Integration of Models in Knowledge Discovery

Ryszard Szupiluk, Tomasz Ząbkowski, Piotr Wojewnik, 2004 .

Zastosowanie reguł asocjacyjnych do analizy danych ankietowych w wybranych obszarach logistyki przedsiębiorstw przetwórstwa rolno-spożywczego. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics, 2013, Nr 279, s. 311-320

Tomasz Ząbkowski, Piotr Jałowiecki, T. Ząbkowski, 2013 .

Revealing Household Characteristics from Electricity Meter Data with Grade Analysis and Machine Learning Algorithms

Mariya A. Sodenkamp, Krzysztof Gajowniczek, Tomasz Ząbkowski, 2018, Applied Sciences.

Interactive Decision Tree Learning and Decision Rule Extraction Based on the ImbTreeEntropy and ImbTreeAUC Packages

Krzysztof Gajowniczek, Tomasz Ząbkowski, T. Zabkowski, 2021, Processes.

ImbTreeAUC: An R package for building classification trees using the area under the ROC curve (AUC) on imbalanced datasets

Krzysztof Gajowniczek, Tomasz Ząbkowski, T. Zabkowski, 2021, SoftwareX.

ImbTreeEntropy and ImbTreeAUC: Novel R Packages for Decision Tree Learning on the Imbalanced Datasets

Krzysztof Gajowniczek, Tomasz Ząbkowski, T. Zabkowski, 2021, Electronics.

Deep Learning-Based Approaches to Optimize the Electricity Contract Capacity Problem for Commercial Customers

Krzysztof Gajowniczek, Tomasz Ząbkowski, Rafik Nafkha, 2021 .

Q-Entropy Approach to Selecting High Income Households

Krzysztof Gajowniczek, Tomasz Ząbkowski, Arkadiusz Orłowski, 2015 .

Mining Associations on the Warsaw Stock Exchange

Tomasz Ząbkowski, Arkadiusz Orłowski, Krzysztof Karpio, 2013 .

Entropy Based Trees to Support Decision Making for Customer Churn Management

Krzysztof Gajowniczek, Tomasz Ząbkowski, Arkadiusz Orłowski, 2016 .