77 citations · 78 across the 5 of their papers we have counts for
7 papers
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…
Model Compression for Dynamic Forecast Combination
Vitor Cerqueira, Luis Torgo, Carlos Soares +1
The predictive advantage of combining several different predictive models is widely accepted. Particularly in time series forecasting problems, this combination is often dynamic to…
STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection
Vitor Cerqueira, Heitor Murilo Gomes, Albert Bifet +1
Concept drift detection is a crucial task in data stream evolving environments. Most of state of the art approaches designed to tackle this problem monitor the loss of predictive m…
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes
Vitor Cerqueira, Luis Torgo, Carlos Soares
The early detection of anomalous events in time series data is essential in many domains of application. In this paper we deal with critical health events, which represent a signif…
VEST: Automatic Feature Engineering for Forecasting
Vitor Cerqueira, Nuno Moniz, Carlos Soares
Time series forecasting is a challenging task with applications in a wide range of domains. Auto-regression is one of the most common approaches to address these problems. Accordin…
Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters
Vitor Cerqueira, Luis Torgo, Carlos Soares
Time series forecasting is one of the most active research topics. Machine learning methods have been increasingly adopted to solve these predictive tasks. However, in a recent wor…