Tag Archives: cross-validation

LM101-076: How To Choose the Best Model using AIC or GAIC

The Model Selection Problem.

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Episode Summary: In this episode, we explain the proper semantic interpretation of the Akaike Information Criterion (AIC) and the Generalized Akaike Information Criterion (GAIC) for the purpose of picking the best model for a given set of training data.  The precise semantic interpretation of these model selection criteria is provided, explicit assumptions are provided for the AIC and… Read More »

LM101-028: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods)[RERUN]

There is no correct interpretation of the identity of an ambiguous letter.

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LM101-028: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods)[RERUN] Episode Summary: In this episode we discuss the problem of how to evaluate the ability of a learning machine to make generalizations and construct abstractions given the learning machine is provided a finite limited collection of experiences. Show Notes: Hello everyone! Welcome to a RERUN of… Read More »

LM101-013: How to Use Linear Machine Learning Software to Make Predictions (Linear Regression Software)

Android classifying a flower in the Iris Dataset.

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Episode Summary: In this episode we describe how to download and use free linear machine learning software to make predictions for classifying flower species using a famous machine learning data set. Show Notes: Hello everyone! Welcome to the thirteenth podcast in the podcast series Learning Machines 101. In this series of podcasts my goal is to discuss important… Read More »

LM101-012: How to Evaluate the Ability to Generalize from Experience (Cross-Validation Methods)

There is no correct interpretation of the identity of an ambiguous letter.

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Episode Summary: In this episode we discuss the problem of how to evaluate the ability of a learning machine to make generalizations and construct abstractions given the learning machine is provided a finite limited collection of experiences. Show Notes: Hello everyone! Welcome to the twelfth podcast in the podcast series Learning Machines 101. In this series of podcasts… Read More »