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1
Intro
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Jeff Heaton
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Problem Definition
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What is Machine Learning?
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Input and Output Format
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Classification & Regression
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How do Models Work?
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Linear Regression The general form of linear regression is
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Temperature Conversion Model
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Training the Model
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Non-Differentiable Models
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Beyond Linear Regression
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Model Similarities
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RBF Neural Network
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Radial Basis Functions
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Gaussian RBF Graph
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RBF Network Diagram
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RBF Network Calculation
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Mutation
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Crossover
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Advanced GA's
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Using my GA Utility
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Artificial Intelligence for Humans
Description:
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.

Detecting Cancer with RBF Networks Trained by Genetic Algorithms

Jeff Heaton
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