1.1k citations · 2k across the 22 of their papers we have counts for
23 papers
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms
Luis Roque, Carlos Soares, Luís Torgo
We introduce the Robustness of Hierarchically Organized Time Series (RHiOTS) framework, designed to assess the robustness of hierarchical time series forecasting models and algorit…
Multi-output Ensembles for Multi-step Forecasting
Vitor Cerqueira, Luis Torgo
This paper studies the application of ensembles composed of multi-output models for multi-step ahead forecasting problems. Dynamic ensembles have been commonly used for forecasting…
Predicting Stellar Rotation Periods Using XGBoost
Nuno R. C. Gomes, Fabio Del Sordo, Luís Torgo
This work aims to develop a computationally inexpensive approach, based on machine learning techniques, to accurately predict thousands of stellar rotation periods. The innovation…
Exceedance Probability Forecasting via Regression for Significant Wave Height Prediction
Vitor Cerqueira, Luis Torgo
Significant wave height forecasting is a key problem in ocean data analytics. This task affects several maritime operations, such as managing the passage of vessels or estimating t…
Automated Imbalanced Classification via Layered Learning
Vitor Cerqueira, Luis Torgo, Paula Branco +1
In this paper we address imbalanced binary classification (IBC) tasks. Applying resampling strategies to balance the class distribution of training instances is a common approach t…
Beyond Average Performance -- exploring regions of deviating performance for black box classification models
Luis Torgo, Paulo Azevedo, Ines Areosa
Machine learning models are becoming increasingly popular in different types of settings. This is mainly caused by their ability to achieve a level of predictive performance that i…