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Part II: Practical Implementations.

Part II: Practical Implementations. Modeling the Classes. Stochastic Discrimination. Algorithm for Training a SD Classifier. Generate projectable weak model. Evaluate model w.r.t. training set, check enrichment. Check uniformity w.r.t. existing collection. Add to discriminant.

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Part II: Practical Implementations.