Enhancing Network Security: A Study on Classification Models for Intrusion Detection Systems by Abeer Abd Alhameed Mahmood, Azhar A. Hadi, Wasan Hashim Al-Masoody

“…It also does better than logistic regression and multi-layer perceptron in multiclass classification. …”
Get full text

Deep hybrid architecture with stacked ensemble learning for binary classification of retinal disease by Priyadharsini C, Asnath Victy Phamila Y

“…Conclusion: This is the first work to experiment with 144 combinations to identify suitable deep architecture for binary retinal disease classification. The study recommends Xception for feature extraction ensembled with ExtraTreeClassifier, Light gradient boosting machine, Random Forest, AdaBoost classifiers, and meta-learner as Logistic Regression. …”
Get full text

Rice Leaf Nutrient Deficiency Classification System Using CAR-Capsule Network by M. Amudha, K. Brindha

“…The classifier’s performance was compared with three prior approaches, including Random Forest Regression with an accuracy of 81.82%, SVM with C-means clustering at 92%, and VGG19 at 91.8%. …”
Get full text

Reservoir type classification and water yield prediction based on petrophysical conversion models by Jiejun Zhu, Jiejun Zhu, Jiejun Zhu, Jian Peng, Jian Peng, Jian Peng, Zhibin Lv, Zhibin Lv, Zhibin Lv, Shuangquan Chen

“…An efficient categorization of reservoir types was accomplished by isolating three key elements from the pseudo capillary pressure curve—displacement pressure, median pressure, and sorting coefficient—and integrating them with the generalized regression neural network. …”
Get full text

Blending Ensemble Learning Model for 12-Lead Electrocardiogram-Based Arrhythmia Classification by Hai-Long Nguyen, Van Su Pham, Hai-Chau Le

“…Experiments conducted with seven diverse machine learning algorithms (Adaptive Boosting, Extreme Gradient Boosting, Decision Trees, k-Nearest Neighbors, Logistic Regression, Random Forest, and Support Vector Machine) demonstrate that the proposed blending solution, utilizing an LR meta-model with three optimal base models, achieves a superior classification accuracy of 96.48%, offering an effective tool for clinical decision support.…”
Get full text

Machine learning for brain tumor classification: evaluating feature extraction and algorithm efficiency by Krishan Kumar, Kiran Jyoti, Krishan Kumar

“…The purpose of this study is to investigates the capability of machine learning algorithms and feature extraction methods to detection and classification of brain tumors. We implemented six machine learning algorithms and three features extraction methods, including Image Loading, HOG, and LBP. …”
Get full text

A Novel Machine Learning Approach: Soil Temperature Ordinal Classification (STOC) by Derya Birant, Pelin Yıldırım Taşer, Cansel Küçük

“…Although some progress has been made in this area, the existing methods provide a regression or nominal classification task. However, ordinal classification is yet to be explored. …”
Get full text

An Optimized Weighted-Voting-Based Ensemble Learning Approach for Fake News Classification by Muhammad Shahzaib Toor, Hooria Shahbaz, Muddasar Yasin, Armughan Ali, Norma Latif Fitriyani, Changgyun Kim, Muhammad Syafrudin

Get full text

An analysis of the latent classification and influencing factors of the characteristic symptoms in patients with maintenance hemodialysis by FENG Meiqin, CHEN Hongfang, ZHANG Jiayang, ZHANG Layin

Get full text

Surrounding Rock Stability Classification Method of Coal Roadway Based on In Situ Stress by Yongjie Yang, Gang Huang, Lingren Meng

Get full text

New hybrid features extracted from US images for breast cancer classification by Gigi Tăbăcaru, Simona Moldovanu, Dan Munteanu, Marian Barbu

Get full text

RASGEF1C methylation for the distinguishment and classification of benign and malignant thyroid tumors by Wenkang Yu, Yifei Yin, Mengxia Li, Haixia Huang, Junjie Li, Yi Zhang, Lun Zhu, Yifen Zhang, Xuandong Huang, Chenxia Jiang, Rongxi Yang

Get full text

Identification of Earthquake Precursors Origin and AI Framework for Automatic Classification for One of These Precursors by Ghada Ali, Lotfy Samy, Omar M. Saad, Ali G. Hafez, El-Sayed Hasaneen, Kamal AbdElrahman, Ibrahim Salah, Mohammed S. Fnais, Hamed Nofel, Ahmed M. Mohamed

“…In instrumental artifacts, the arrival is taken after the precursory and before it in the case of the natural ground-based pattern. The examined classification topologies are Logistic Regression (LR), K-nearest neighbors Classifier (KNN), Support Vector Machine (SVM), Decision Tree Classifier (DT), Random Forest Classifier (RF), XGB Classifier, Naïve Bayes (NB), Voting Classifier and Convolutional Neural Network (CNN). …”
Get full text

Leveraging cancer mutation data to inform the pathogenicity classification of germline missense variants. by Bushra Haque, David Cheerie, Amy Pan, Meredith Curtis, Thomas Nalpathamkalam, Jimmy Nguyen, Celine Salhab, Bhooma Thiruvahindrapuram, Jade Zhang, Madeline Couse, Taila Hartley, Michelle M Morrow, E Magda Price, Susan Walker, David Malkin, Frederick P Roth, Gregory Costain

“…The odds ratio for a likely pathogenic/pathogenic classification in ClinVar was 28.3 (95% confidence interval: 24.2-33.1, p < 0.001), compared with all other germline missense variants in the same 216 genes. …”
Get full text

A novel hybrid vision UNet architecture for brain tumor segmentation and classification by M. Renugadevi, K. Narasimhan, K. Ramkumar, N. Raju

Get full text

Comparative Analysis of Different Efficient Machine Learning Methods for Fetal Health Classification by Md Takbir Alam, Md Ashibul Islam Khan, Nahian Nakiba Dola, Tahia Tazin, Mohammad Monirujjaman Khan, Amani Abdulrahman Albraikan, Faris A. Almalki

Get full text

Comparison of ECG Between Gameplay and Seated Rest: Machine Learning-Based Classification by Emi Yuda, Hiroyuki Edamatsu, Yutaka Yoshida, Takahiro Ueno

“…Among all models, OCS with k = 3 achieved the highest classification accuracy for both 5 min and 10 min data. …”
Get full text

Analysis of influencing factors and mechanism of classification accuracy of personal waste of urban residents by Ruike Ye, Mengying Bian, Keqi Yi, Yuxin Liu, Qingwei Zeng, Jianuo Zhang

Get full text

Machine Learning for Enhanced COPD Diagnosis: A Comparative Analysis of Classification Algorithms by Walaa H. Elashmawi, Adel Djellal, Alaa Sheta, Salim Surani, Sultan Aljahdali

Get full text

Utilization of Classification Learning Algorithms for Upper-Body Non-Cyclic Motion Prediction by Bon H. Koo, Ho Chit Siu, Dava J. Newman, Ellen T. Roche, Lonnie G. Petersen

Get full text