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Detalhes

Detalhes

  • Nome

    Pedro Strecht
  • Cluster

    Informática
  • Cargo

    Investigador Colaborador Externo
  • Desde

    01 abril 2014
Publicações

2022

Density Estimation in High-Dimensional Spaces: A Multivariate Histogram Approach

Autores
Strecht, P; Mendes Moreira, J; Soares, C;

Publicação
ADVANCED DATA MINING AND APPLICATIONS, ADMA 2022, PT II

Abstract

2021

Inmplode: A framework to interpret multiple related rule-based models

Autores
Strecht, P; Mendes Moreira, J; Soares, C;

Publicação
EXPERT SYSTEMS

Abstract

2015

A Comparative Study of Regression and Classification Algorithms for Modelling Students' Academic Performance

Autores
Strecht, P; Cruz, L; Soares, C; Moreira, JM; Abreu, R;

Publicação
Proceedings of the 8th International Conference on Educational Data Mining, EDM 2015, Madrid, Spain, June 26-29, 2015

Abstract

2014

Merging Decision Trees: A Case Study in Predicting Student Performance

Autores
Strecht, P; Mendes Moreira, J; Soares, C;

Publicação
ADVANCED DATA MINING AND APPLICATIONS, ADMA 2014

Abstract
Predicting the failure of students in university courses can provide useful information for course and programme managers as well as to explain the drop out phenomenon. While it is important to have models at course level, their number makes it hard to extract knowledge that can be useful at the university level. Therefore, to support decision making at this level, it is important to generalize the knowledge contained in those models. We propose an approach to group and merge interpretable models in order to replace them with more general ones without compromising the quality of predictive performance. We evaluate our approach using data from the U. Porto. The results obtained are promising, although they suggest alternative approaches to the problem.