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* Generating frequent k-length item sets * Generating rules based on frequent item sets * Algorithm has exponential complexity, be aware of it * Apriori algorithm is split into apriori and candidates method * Second step rule generation is implemented by rules method * Internal methods are invoked for fine grain unit tests * Wikipedia's train samples and an alternative are provided for test cases * Small documentation for public interface is also shipped |
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association | ||
classification | ||
clustering | ||
cross-validation | ||
datasets | ||
feature-extraction | ||
metric | ||
neural-network | ||
preprocessing | ||
regression | ||
workflow |