For example, feature scaling can help algorithms such as k-means clustering, linear regression, logistic regression, support vector machines, and neural networks. Add your perspective ...

In this repository I'm supposed to come up with written-from-scratch algorithms to perform the following computer vision tasks specifically in python: Feature detectors - Identify the interest points ...

mappings is an array of paths and methods used to generate dimensions for the vector. if it is a path (for example, 'bar.baz' would be the path to true in source1), it will return an enumerable value.

This paper focuses on feature selection methods for support vector machine (SVM) classifiers, checking their optimality by comparing them with some statistical and baseline methods. To achieve the ...

Sparse support vector regression (SSVR) is an effective regression technique. It has been successfully applied to many practical problems. However, it remains challenging to handle the large-scale ...

Sparse support vector regression (SSVR) is an effective regression technique. It has been successfully applied to many practical problems. However, it remains challenging to handle the large-scale ...