[HTML][HTML] Impact of the learners diversity and combination method on the generation of heterogeneous classifier ensembles
Ensembles of classifiers is a proven approach in machine learning with a wide variety of
research works. The main issue in ensembles of classifiers is not only the selection of the …
research works. The main issue in ensembles of classifiers is not only the selection of the …
Analisis Perbandingan Algoritma Optimasi pada Random Forest untuk Klasifikasi Data Bank Marketing
The world of banking requires a marketer to be able to reduce the risk of borrowing by
keeping his customers from occurring non-performing loans. One way to reduce this risk is …
keeping his customers from occurring non-performing loans. One way to reduce this risk is …
Tackling feature selection problems with genetic algorithms in software defect prediction for optimization
RB Bahaweres, AI Suroso, AW Hutomo… - 2020 International …, 2020 - ieeexplore.ieee.org
Software defect prediction is a way to improve quality by finding and tracking defective
modules in the software which helps reduce costs during the software testing process. The …
modules in the software which helps reduce costs during the software testing process. The …
Applying machine learning to carotid sonographic features for recurrent stroke in patients with acute stroke
SY Lin, KM Law, YC Yeh, KC Wu, JH Lai… - Frontiers in …, 2022 - frontiersin.org
Background Although carotid sonographic features have been used as predictors of
recurrent stroke, few large-scale studies have explored the use of machine learning analysis …
recurrent stroke, few large-scale studies have explored the use of machine learning analysis …
Integrating MTS with bagging strategy for class imbalance problems
Class imbalance is a common problem in classification tasks. The learning schemes of most
classification algorithms tend to optimize the overall accuracy, and thus, identification of …
classification algorithms tend to optimize the overall accuracy, and thus, identification of …
DF-dRVFL: A novel deep feature based classifier for breast mass classification
Amongst all types of cancer, breast cancer has become one of the most common cancers in
the UK threatening millions of people's health. Early detection of breast cancer plays a key …
the UK threatening millions of people's health. Early detection of breast cancer plays a key …
Deep learning based ensemble approach to predict student academic performance: case study
YK Salal, SM Abdullaev - 2020 3rd International conference on …, 2020 - ieeexplore.ieee.org
Traditional practices of education, medicine, and economics often use collective expert
methods to find acceptable solutions to complex issues. The computer model of such …
methods to find acceptable solutions to complex issues. The computer model of such …
[HTML][HTML] Mathematical model for preoperative differential diagnosis for the parathyroid neoplasms
JA Krupinova, AR Elfimova, OY Rebrova… - Journal of Pathology …, 2022 - Elsevier
Background and objective Preoperative diagnosis of parathyroid carcinoma (PC) is critical
for the determination of the scope of surgical intervention. Nowadays, specific diagnostic …
for the determination of the scope of surgical intervention. Nowadays, specific diagnostic …
Cluster-based under-sampling using farthest neighbour technique for imbalanced datasets
In domain of data mining, learning from imbalanced class distribution datasets is a
challenging problem for conventional classifiers. The class imbalance exists when the …
challenging problem for conventional classifiers. The class imbalance exists when the …
Genre Classification of Movies from a Single Poster Image Using Feature Fusion
F Nadem, R Mahdian, H Zareian - 2021 7th International …, 2021 - ieeexplore.ieee.org
The movie industry is one of the largest and most influential sectors of any community. Each
movie in the industry consists of different elements such as actors, directors, preparation …
movie in the industry consists of different elements such as actors, directors, preparation …