Suppose I'm using the Spambase dataset, with 57 real continuous variables and one binary label, and I'd like to implement the Find-S or LGG or similar algorithms. How do I represent the dataset for usage in the algorithm? I've tried binning by standard deviation, binning by heuristics. Is there an adaption for concept learning for continuous variables?

Utilizing continuous variables in concept learning algorithms

Artificial Intelligence Asked by Edwin Carlsson on December 3, 2020

Suppose I’m using the Spambase dataset, with 57 real continuous variables and one binary label, and I’d like to implement the Find-S or LGG or similar algorithms.

How do I represent the dataset for usage in the algorithm? I’ve tried binning by standard deviation, binning by heuristics.
Is there an adaption for concept learning for continuous variables?

concept learning find s learning theory machine learning

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