Predictive modeling of the ratings of perceived exertion during training and competition in professional soccer players.

Objectives: Evaluate the ability of predicting the ratings of perceived exertion from the external load variables in professional soccer players through a chronological perspective (i.e., past features values are considered additional features) through machine learning models by considering the playing position.

Uncertain imputation for time-series forecasting: Application to COVID-19 daily mortality prediction.

The object of this study is to put forward uncertainty modeling associated with missing time series data imputation in a predictive context. We propose three imputation methods associated with uncertainty modeling. These methods are evaluated on a COVID-19 dataset out of which some values have been randomly removed.

The Use of Fitness-Fatigue Models for Sport Performance Modelling: Conceptual Issues and Contributions from Machine-Learning.

The emergence of the first Fitness-Fatigue impulse responses models (FFMs) have allowed the sport science community to investigate relationships between the effects of training and performance. In the models, athletic performance is described by first order transfer functions which represent Fitness and Fatigue antagonistic responses to training. On this basis, the mathematical structure allows for a precise determination of optimal sequence of training doses that would enhance the greatest athletic performance, at a given time point.

EBCR: Empirical Bayes concordance ratio method to improve similarity measurement in memory-based collaborative filtering.

Recommender systems aim to provide users with a selection of items, based on predicting their preferences for items they have not yet rated, thus helping them filter out irrelevant ones from a large product catalogue. Collaborative filtering is a widely used mechanism to predict a particular user's interest in a given item, based on feedback from neighbour users with similar tastes. The way the user's neighbourhood is identified has a significant impact on prediction accuracy.