Explore a presentation on detecting cancer using a Radial Basis Function (RBF) Network trained by a Genetic Algorithm. Learn about the winning entry in the Society of Actuaries 2013 Forecasting & Futurism genetic algorithm contest, which utilized a multi-threaded C# based genetic algorithm for training. Dive into machine learning concepts, including classification, regression, and linear regression models. Discover the workings of RBF Neural Networks, including radial basis functions and Gaussian RBF graphs. Gain insights into genetic algorithm techniques such as mutation, crossover, and advanced GA implementations. Understand how to use a GA utility for practical applications in artificial intelligence and healthcare.
Overview
Syllabus
Intro
Jeff Heaton
Problem Definition
What is Machine Learning?
Input and Output Format
Classification & Regression
How do Models Work?
Linear Regression The general form of linear regression is
Temperature Conversion Model
Training the Model
Non-Differentiable Models
Beyond Linear Regression
Model Similarities
RBF Neural Network
Radial Basis Functions
Gaussian RBF Graph
RBF Network Diagram
RBF Network Calculation
Mutation
Crossover
Advanced GA's
Using my GA Utility
Artificial Intelligence for Humans
Taught by
Jeff Heaton
