Radial Basis Functions: Types, Advantages, and Use Casesby@sanjaykn170396
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8,373 reads

Radial Basis Functions: Types, Advantages, and Use Cases

by Sanjay Kumar6mJanuary 24th, 2023
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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.
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Sanjay Kumar

Sanjay Kumar

@sanjaykn170396

Data scientist | ML Engineer | Statistician

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Sanjay Kumar@sanjaykn170396
Data scientist | ML Engineer | Statistician

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