Simple TM

A pure Python, simpler implementation of the TM models.

BaseTM(n_clauses, T, s, dim, n_classes[, q, ...])	Weighted Tsetlin Machine in pure numpy.
MultiClassTM(n_clauses, T, s, dim, n_classes)	TM for multi-class classification: each sample has exactly one of n_classes classes.
MultiOutputTM(n_clauses, T, s, dim, n_classes)	TM for multi-label classification: each sample can have any number of n_classes labels.
BinaryTM(n_clauses, T, s, dim, **opt)	TM for binary classification: one output, each sample is 0 or 1.
RegressionTM(n_clauses, T, s, dim, y_range, ...)	TM for regression: one real-valued target per sample (Regression TM).