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 ...

Abstract: In this paper, the performance of different SVM kernel functions (Polynomial, Linear and Gaussian) for modelling electricity and hydrogen production in the gas turbine cycle ...

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 ...

The KernelPlugin.from_directory method says (emphasis mine): A .py file is parsed and a plugin created, the functions within as [sic] then combined with any other functions found. The python file ...

Abstract: Support Vector Machines, a new generation learning system based on recent advances in statistical learning theory deliver state-of-the-art performance in real-world applications such as text ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

Python 3.11 introduced the Specializing Adaptive Interpreter. When the interpreter detects that some operations predictably involve the same types, those operations are “specialized.” The generic ...