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06/26/2023
Multi-output Ensembles for Multi-step Forecasting
This paper studies the application of ensembles composed of multi-output...
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06/20/2022
Exceedance Probability Forecasting via Regression for Significant Wave Height Forecasting
Significant wave height forecasting is a key problem in ocean data analy...
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05/05/2022
Automated Imbalanced Classification via Layered Learning
In this paper we address imbalanced binary classification (IBC) tasks. A...
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12/29/2021
AutoFITS: Automatic Feature Engineering for Irregular Time Series
A time series represents a set of observations collected over time. Typi...
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04/05/2021
Model Compression for Dynamic Forecast Combination
The predictive advantage of combining several different predictive model...
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04/01/2021
Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators
Evaluating predictive models is a crucial task in predictive analytics. ...
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03/01/2021
STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection
Concept drift detection is a crucial task in data stream evolving enviro...
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10/22/2020
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes
The early detection of anomalous events in time series data is essential...
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10/14/2020
VEST: Automatic Feature Engineering for Forecasting
Time series forecasting is a challenging task with applications in a wid...
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09/29/2019
Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters
Time series forecasting is one of the most active research topics. Machi...
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05/28/2019
Evaluating time series forecasting models: An empirical study on performance estimation methods
Performance estimation aims at estimating the loss that a predictive mod...
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03/14/2018
How to evaluate sentiment classifiers for Twitter time-ordered data?
Social media are becoming an increasingly important source of informatio...
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06/28/2017
