Black hole algorithm: A comprehensive survey
This paper provides an in-depth literature review of the Black Hole Algorithm (BHA) which is
considered as a recent metaheuristic. BHA has been proven to be very efficient in different …
considered as a recent metaheuristic. BHA has been proven to be very efficient in different …
Attention based GRU-LSTM for software defect prediction
HS Munir, S Ren, M Mustafa, CN Siddique, S Qayyum - Plos one, 2021 - journals.plos.org
Software defect prediction (SDP) can be used to produce reliable, high-quality software. The
current SDP is practiced on program granular components (such as file level, class level, or …
current SDP is practiced on program granular components (such as file level, class level, or …
Transfer learning for cross-company software defect prediction
CONTEXT: Software defect prediction studies usually built models using within-company
data, but very few focused on the prediction models trained with cross-company data. It is …
data, but very few focused on the prediction models trained with cross-company data. It is …
Machine learning based mobile malware detection using highly imbalanced network traffic
In recent years, the number and variety of malicious mobile apps have increased drastically,
especially on Android platform, which brings insurmountable challenges for malicious app …
especially on Android platform, which brings insurmountable challenges for malicious app …
Software defect prediction via attention‐based recurrent neural network
G Fan, X Diao, H Yu, K Yang, L Chen - Scientific Programming, 2019 - Wiley Online Library
In order to improve software reliability, software defect prediction is applied to the process of
software maintenance to identify potential bugs. Traditional methods of software defect …
software maintenance to identify potential bugs. Traditional methods of software defect …
Multi-view ensemble learning based on distance-to-model and adaptive clustering for imbalanced credit risk assessment in P2P lending
Credit risk assessment is a crucial task in the peer-to-peer (P2P) lending industry. In recent
years, ensemble learning methods have been verified to perform better in default prediction …
years, ensemble learning methods have been verified to perform better in default prediction …
Negative samples reduction in cross-company software defects prediction
Context Software defect prediction has been widely studied based on various machine-
learning algorithms. Previous studies usually focus on within-company defects prediction …
learning algorithms. Previous studies usually focus on within-company defects prediction …
AFNFS: Adaptive fuzzy neighborhood-based feature selection with adaptive synthetic over-sampling for imbalanced data
L Sun, M Li, W Ding, E Zhang, X Mu, J Xu - Information Sciences, 2022 - Elsevier
The classification efficiency of majority classes for imbalanced data is so concerned in real-
world applications. Almost fuzzy neighborhood radius still needs to be manually set and …
world applications. Almost fuzzy neighborhood radius still needs to be manually set and …
Unsupervised band selection of medical hyperspectral images guided by data gravitation and weak correlation
C Zhang, Z Zhang, D Yu, Q Cheng, S Shan, M Li… - Computer Methods and …, 2023 - Elsevier
Abstract Background and Objective Medical hyperspectral images (MHSIs) are used for a
contact-free examination of patients without harmful radiation. However, high-dimensionality …
contact-free examination of patients without harmful radiation. However, high-dimensionality …
Weighted data gravitation classification for standard and imbalanced data
Gravitation is a fundamental interaction whose concept and effects applied to data
classification become a novel data classification technique. The simple principle of data …
classification become a novel data classification technique. The simple principle of data …