Multi-label Stream Classification Software and Datasets

Access HERE source code and datasets from our contribution (Cerri et al., 2021) presented in the 36th ACM Symposium on Applied Computing (2021). In this contribution, we propose an online unsupervised incremental method based on self-organizing maps for multi-label stream classification in scenarios with infinitely delayed labels.

Acess HERE source code and datasets from our contribution (Cerri et al., 2022) presented in the 21st IEEE International Conference on Machine Learning and Applications (2022). In this contribution, we extended our previous work proposing an algorithm adaptation-based self-organizing map. It is also an online unsupervised incremental method for multi-label stream classification in scenarios with infinitely delayed labels.

Hierarchical Multi-Label Software and Datasets

Access HERE source code and datasets for the following HMC methods:
- Hierachical Multi-label Classification with a Genetic Algorithm (HMC-GA), as described by Cerri et al., 2019
- Hierarchical Multi-label Classification with Neural Networks, as described by Cerri et al., 2015 and Cerri et al., 2016

Introduction to Neural Networks - ERAMIA 2020 Mini-Course (Portuguese)

Access the presentations and R notebooks related to the mini-course given at ERAMIA 2020. Access the material HERE!