The new ensemble SVM can improve the performance of single binary-tree SVM. At the end, the new algorithm is applied to fault diagnosis of blast furnace faults and the Tennessee Eastman process (TEP).

Support Vector Machine (SVM) is a supervised machine learning algorithm with strong classification capabilities. It works by optimizing the margin between data groups, which enhances accuracy and ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. A supervised machine learning model has been developed that allows for the prediction ...

The fundamental structure of the data distribution is exploited by clustering algorithms, which also provide criteria for categorizing data that have matching features [2]. K-Means, also known as ...

Angiogenesis, the formation of new blood vessels, is a fundamental biological process with implications for both physiological functions and pathological conditions. While the transcriptional ...

PyRadiomics in Python was used for feature extraction ... our study built and validated six machine learning algorithms, including support vector machine (SVM), logistic regression (LR), extreme ...

The performance of five machine learning algorithms (logistic regression, support vector machine, random forest, XGBoost and CatBoost) was evaluated using accuracy, sensitivity, specificity, positive ...