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Ing. Peter Gnip, PhD.

Ing. Peter Gnip, PhD.

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Peter Gnip received his M.Sc. and Ph.D. degrees in Informatics from the Technical University of Kosice, Slovakia, in 2018 and 2021, respectively. Actually, he is an assistant professor at the Department of Computers and Informatics, Technical University of Kosice. His research focuses on applying machine learning approaches to strongly imbalanced data.

Research interests:
  • Bankruptcy prediction, decision support for digital business
  • Imbalanced learning
Projects:
Publications:

2023

R. Kanász, P. Gnip, M. Zoričák, P. Drotár

Bankruptcy prediction using ensemble of autoencoders optimized by genetic algorithm

Journal: PeerJ. Computer science.

2021

P. Gnip, L. Vokorokos, P. Drotár

Selective oversampling approach for strongly imbalanced data

Journal: PeerJ. Computer science.

2020

M. Zoričák, P. Gnip, P. Drotár, V. Gazda

Bankruptcy prediction for small- and medium-sized companies using severely imbalanced datasets

Journal: Economic Modelling

P. Gnip, P. Drotár

Ensemble methods for strongly imbalanced data: Bankruptcy prediction

Journal: 17th International Symposium on Intelligent Systems and Informatics

2019

P. Drotár, P. Gnip, M. Zoričák, V. Gazda

Small- and medium-enterprises bankruptcy dataset

Journal: Data in Brief.

P. Bugata, P. Gnip, P. Drotár

Stability analysis of WkNN feature selection

Journal: Applied Computational Intelligence and Informatics.

2018

P. Drotár, P. Gnip, M. Zoričák, V. Gazda

Single-Class Bankruptcy Prediction Based on the Data from Annual Reports

Journal: Intelligent data engineering and automated learning