The core idea of LCQHNN is to center on quantum feature amplification (Quantum Feature Amplification) while combining a classical stability optimization strategy, establishing an efficient information ...
Abstract: Over the years, researchers have proposed numerous Twin Support Vector Machines (TSVM) variants aimed at addressing diverse challenges. These variants encompass sparse TSVM models, robust ...
In this project, We build a Support Vector Machines classifier to classify a Pulsar star. We have used the Predicting a Pulsar Star dataset for this project. We have downloaded this dataset from the ...
The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...
ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...
1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and ...
Abstract: The Projection Twin Support Vector Machine (PTSVM) and its variant, the Least Squares PTSVM (LSPTSVM), have demonstrated significant effectiveness in supervised classification tasks due to ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback