Radial Basis Functions: Types, Advantages, and Use Cases


Too Long; Didn’t Read

This article explains the basic intuition, mathematical idea & scope of radial basis function in the development of predictive machine learning models. The Radial Basis function is a mathematical function that takes a real-valued input and outputs areal-valued output based on the distance between the input value projected in space from an imaginary fixed point placed elsewhere. This function is popularly used in many machine learning and deep learning algorithms.

L O A D I N G
. . . comments & more!


Too Long; Didn’t Read

This article explains the basic intuition, mathematical idea & scope of radial basis function in the development of predictive machine learning models. The Radial Basis function is a mathematical function that takes a real-valued input and outputs areal-valued output based on the distance between the input value projected in space from an imaginary fixed point placed elsewhere. This function is popularly used in many machine learning and deep learning algorithms.

L O A D I N G
. . . comments & more!

FOLLOW US ON GOOGLE NEWS

Read original article here

Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to their authors. If you are the owner of the content and do not want us to publish your materials, please contact us by email – admin@technoblender.com. The content will be deleted within 24 hours.
AdvantagesBasisCasesFunctionsRadialTech NewsTechnoblenderTechnologytypes
Comments (0)
Add Comment