Finding the best learning to rank algorithms for effort-aware defect prediction
Abstract Context: Effort-Aware Defect Prediction (EADP) ranks software modules or changes
based on their predicted number of defects (ie, considering modules or changes as effort) or …
based on their predicted number of defects (ie, considering modules or changes as effort) or …
Trusted detection of ransomware in a private cloud using machine learning methods leveraging meta-features from volatile memory
Cloud computing is one of today's most popular and important IT trends. Currently, most
organizations use cloud computing services (public or private) as part of their computer …
organizations use cloud computing services (public or private) as part of their computer …
Soil erosion susceptibility mapping using ensemble machine learning models: A case study of upper Congo river sub-basin
Despite its large size, the Congo Basin (CB), which spans ten countries, has remained an
area of particular interest for scientific discovery due to gaps in Earth science, environmental …
area of particular interest for scientific discovery due to gaps in Earth science, environmental …
Polynomial-based radial basis function neural networks (P-RBF NNs) realized with the aid of particle swarm optimization
In this study, we design polynomial-based radial basis function neural networks (P-RBF
NNs) based on a fuzzy inference mechanism. The essential design parameters (including …
NNs) based on a fuzzy inference mechanism. The essential design parameters (including …
Randomized controlled trial of OnTrack, a just-in-time adaptive intervention designed to enhance weight loss
Individual instances of nonadherence to reduced calorie dietary prescriptions, that is, dietary
lapses, represent a key challenge for weight management. Just-in-time adaptive …
lapses, represent a key challenge for weight management. Just-in-time adaptive …
SFEM: Structural feature extraction methodology for the detection of malicious office documents using machine learning methods
Office documents are used extensively by individuals and organizations. Most users
consider these documents safe for use. Unfortunately, Office documents can contain …
consider these documents safe for use. Unfortunately, Office documents can contain …
A linear model based on Kalman filter for improving neural network classification performance
Neural network has been applied in several classification problems such as in medical
diagnosis, handwriting recognition, and product inspection, with a good classification …
diagnosis, handwriting recognition, and product inspection, with a good classification …
OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses
Given that the overarching goal of weight loss programs is to remain adherent to a dietary
prescription, specific moments of nonadherence known as “dietary lapses” can threaten …
prescription, specific moments of nonadherence known as “dietary lapses” can threaten …
Ensemble learning approach to motor imagery EEG signal classification
R Chatterjee, A Datta, DK Sanyal - … Learning in Bio-Signal Analysis and …, 2019 - Elsevier
Brain-computer interface (BCI) is an alternative communication pathway between the human
brain and computer system without involving any muscles or actual motor neuron activities …
brain and computer system without involving any muscles or actual motor neuron activities …
Robust subspace clustering based on automatic weighted multiple kernel learning
L Guo, X Zhang, Z Liu, X Xue, Q Wang, S Zheng - Information Sciences, 2021 - Elsevier
Multiple kernel learning (MKL), which combines a set of prespecified basic kernels to
improve the clustering performance, has become an important research topic. Unfortunately …
improve the clustering performance, has become an important research topic. Unfortunately …