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Soft independent modelling of class analogies
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<p>Soft independent modelling by class analogy (SIMCA) is a <a href="/facts/Statistics/DNPsKGYU">statistical</a> method for <a href="/facts/Supervised_learning/JlNFNPFt">supervised classification</a> of data. The method requires a <a href="/facts/Training_data_set/V3mMQb2G">training data set</a> consisting of samples (or objects) with a set of attributes and their class membership. The term soft refers to the fact the classifier can identify samples as belonging to multiple classes and not necessarily producing a classification of samples into non-overlapping classes. </p>