[HTML][HTML] Stability of feature selection algorithm: A review

UM Khaire, R Dhanalakshmi - Journal of King Saud University-Computer …, 2022 - Elsevier
Feature selection technique is a knowledge discovery tool which provides an understanding
of the problem through the analysis of the most relevant features. Feature selection aims at …

Machine learning for streaming data: state of the art, challenges, and opportunities

HM Gomes, J Read, A Bifet, JP Barddal… - ACM SIGKDD …, 2019 - dl.acm.org
Incremental learning, online learning, and data stream learning are terms commonly
associated with learning algorithms that update their models given a continuous influx of …

[HTML][HTML] Deterministic local interpretable model-agnostic explanations for stable explainability

MR Zafar, N Khan - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
Local Interpretable Model-Agnostic Explanations (LIME) is a popular technique used to
increase the interpretability and explainability of black box Machine Learning (ML) …

[HTML][HTML] Benchmark for filter methods for feature selection in high-dimensional classification data

A Bommert, X Sun, B Bischl, J Rahnenführer… - … Statistics & Data Analysis, 2020 - Elsevier
Feature selection is one of the most fundamental problems in machine learning and has
drawn increasing attention due to high-dimensional data sets emerging from different fields …

Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer's disease: a feature selection ensemble combining stability and predictability

T Pereira, FL Ferreira, S Cardoso, D Silva… - BMC medical informatics …, 2018 - Springer
Abstract Background Predicting progression from Mild Cognitive Impairment (MCI) to
Alzheimer's Disease (AD) is an utmost open issue in AD-related research …