This research evaluates the application of Echo State Networks (ESN) for predicting Parkinson’s disease using voice features. The study aims to develop a diagnostic model that ensures high accuracy and…
Continue readingThe article introduces a new framework for feature selection in machine learning models. The approach uses a feature masking method, allowing the same model to be used during feature selection,…
Continue readingThe article presents LLpowershap, a novel feature selection method that uses loss-based Shapley values to identify informative features and reduce noise. The method also demonstrates higher or equal predictive performance…
Continue readingThe article presents MERBench, a unified evaluation benchmark for multimodal emotion recognition. It addresses the problem of inconsistencies in feature extractors, evaluation methods, and experimental settings in emotion recognition research….
Continue readingThis study presents a new ensemble approach for feature selection in time series forecasting, particularly in non-stationary and limited sample scenarios. The approach utilizes a hierarchical structure to exploit feature…
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