Over‐optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results
C Nießl, M Herrmann, C Wiedemann… - … : Data Mining and …, 2022 - Wiley Online Library
In recent years, the need for neutral benchmark studies that focus on the comparison of
methods coming from computational sciences has been increasingly recognized by the …
methods coming from computational sciences has been increasingly recognized by the …
Meta-features for meta-learning
Meta-learning is increasingly used to support the recommendation of machine learning
algorithms and their configurations. These recommendations are made based on meta-data …
algorithms and their configurations. These recommendations are made based on meta-data …
Performance evaluation of best feature subsets for crop yield prediction using machine learning algorithms
MG PS - Applied Artificial Intelligence, 2019 - Taylor & Francis
The rapid innovations and liberalized market economy in agriculture demand accuracy in
Crop Yield Prediction (CYP). In accurate prediction, machine learning (ML) algorithms and …
Crop Yield Prediction (CYP). In accurate prediction, machine learning (ML) algorithms and …
FeatureSelect: a software for feature selection based on machine learning approaches
Y Masoudi-Sobhanzadeh, H Motieghader… - BMC …, 2019 - Springer
Background Feature selection, as a preprocessing stage, is a challenging problem in
various sciences such as biology, engineering, computer science, and other fields. For this …
various sciences such as biology, engineering, computer science, and other fields. For this …
[HTML][HTML] VALIDATE: A deep dive into vulnerability prediction datasets
M Esposito, D Falessi - Information and Software Technology, 2024 - Elsevier
Context: Vulnerabilities are an essential issue today, as they cause economic damage to the
industry and endanger our daily life by threatening critical national security infrastructures …
industry and endanger our daily life by threatening critical national security infrastructures …
An integration of feature extraction and guided regularized random forest feature selection for smartphone based human activity recognition
Abstract Human Activity Recognition (HAR) is an eminent area of research due to its
extensive scope of applications in remote health monitoring, sports, smart home, and many …
extensive scope of applications in remote health monitoring, sports, smart home, and many …
An enhanced J48 classification algorithm for the anomaly intrusion detection systems
S Aljawarneh, MB Yassein, M Aljundi - Cluster Computing, 2019 - Springer
In this paper, we have developed an enhanced J48 algorithm, which uses the J48 algorithm
for improving the detection accuracy and the performance of the novel IDS technique. This …
for improving the detection accuracy and the performance of the novel IDS technique. This …
Gene selection using hybrid multi-objective cuckoo search algorithm with evolutionary operators for cancer microarray data
Microarray data play a huge role in recognizing a proper cancer diagnosis and
classification. In most microarray data set consist of thousands of genes, but the majority …
classification. In most microarray data set consist of thousands of genes, but the majority …
Modeling generalization in machine learning: A methodological and computational study
As machine learning becomes more and more available to the general public, theoretical
questions are turning into pressing practical issues. Possibly, one of the most relevant …
questions are turning into pressing practical issues. Possibly, one of the most relevant …
Permutation importance based modified guided regularized random forest in human activity recognition with smartphone
Abstract Human Activity Recognition (HAR) is a burgeoning field of study due to its real-life
applications in the medical field, the e-health system, and elder care or care of physically …
applications in the medical field, the e-health system, and elder care or care of physically …