Comparative analysis of heart disease prediction using logistic regression, SVM, KNN, and random forest with cross-validation for improved accuracy
Abstract This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and achieves higher accuracy than the baseline model. The novelty lies in the data preparation...
Saved in:
| Main Authors: | Yagyanath Rimal, Navneet Sharma, Siddhartha Paudel, Abeer Alsadoon, Madhav Parsad Koirala, Sumeet Gill |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-93675-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students
by: Yagyanath Rimal, et al.
Published: (2025-04-01) -
Interpretable prediction of stroke prognosis: SHAP for SVM and nomogram for logistic regression
by: Kun Guo, et al.
Published: (2025-03-01) -
Sentiment Analysis of Rohingya Refugees in Aceh using Support Vector Machine (SVM) and Multinomial Logistic Regression
by: Gigih Army Buana Baliputra, et al.
Published: (2025-05-01) -
Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks
by: Nadia Shamshad, et al.
Published: (2025-01-01) -
Classification of Red Foxes: Logistic Regression and SVM with VGG-16, VGG-19, and Inception V3
by: Brian Sabayu, et al.
Published: (2025-05-01)