pyTsetlinMachine package

Submodules

pyTsetlinMachine.tm module

class pyTsetlinMachine.tm.CConvolutionalTsetlinMachine

Bases: _ctypes.Structure

class pyTsetlinMachine.tm.CEmbeddingTsetlinMachine

Bases: _ctypes.Structure

class pyTsetlinMachine.tm.CIndexedTsetlinMachine

Bases: _ctypes.Structure

class pyTsetlinMachine.tm.CMultiClassConvolutionalTsetlinMachine

Bases: _ctypes.Structure

class pyTsetlinMachine.tm.ConvolutionalEmbeddingTsetlinMachine2D(number_of_clauses, T, s, patch_dim, boost_true_positive_feedback=1, number_of_state_bits=8, weighted_clauses=False, s_range=False)

Bases: object

clause_sharing(class_1, class_2)

fit(X, Y, epochs=100, incremental=False)

get_state()

predict(X)

set_state(state)

ta_action(clause, ta)

ta_state(clause, ta)

transform(X, inverted=True)

class pyTsetlinMachine.tm.EmbeddingTsetlinMachine(number_of_clauses, T, s, boost_true_positive_feedback=1, number_of_state_bits=8, weighted_clauses=False, s_range=False)

Bases: object

clause_sharing(class_1, class_2)

fit(X, Y, epochs=100, incremental=False)

get_state()

predict(X)

set_state(state)

ta_action(clause, ta)

ta_state(clause, ta)

transform(X, inverted=True)

class pyTsetlinMachine.tm.MultiClassConvolutionalTsetlinMachine2D(number_of_clauses, T, s, patch_dim, boost_true_positive_feedback=1, number_of_state_bits=8, append_negated=True, weighted_clauses=False, s_range=False, clause_drop_p=0.0, literal_drop_p=0.0)

Bases: object

This class creates a convolutional Tsetlin machine

fit(X, Y, epochs=100, incremental=False)

get_state()

predict(X)

set_state(state_list)

ta_action(mc_tm_class, clause, ta)

ta_state(mc_tm_class, clause, ta)

transform(X, inverted=True)

class pyTsetlinMachine.tm.MultiClassTsetlinMachine(number_of_clauses, T, s, boost_true_positive_feedback=1, number_of_state_bits=8, indexed=True, append_negated=True, weighted_clauses=False, s_range=False, clause_drop_p=0.0, literal_drop_p=0.0)

Bases: object

Docstring for class MultiClassTsetlinMachine.

fit(X, Y, epochs=100, incremental=False)

get_state()

predict(X)

set_state(state_list)

ta_action(mc_tm_class, clause, ta)

ta_state(mc_tm_class, clause, ta)

transform(X, inverted=True)

class pyTsetlinMachine.tm.RegressionTsetlinMachine(number_of_clauses, T, s, boost_true_positive_feedback=1, number_of_state_bits=8, weighted_clauses=False, s_range=False)

Bases: object

fit(X, Y, epochs=100, incremental=False)

get_state()

predict(X)

set_state(state)

pyTsetlinMachine.tm.ctm_pointer

alias of pyTsetlinMachine.tm.LP_CConvolutionalTsetlinMachine

pyTsetlinMachine.tm.etm_pointer

alias of pyTsetlinMachine.tm.LP_CEmbeddingTsetlinMachine

pyTsetlinMachine.tm.itm_pointer

alias of pyTsetlinMachine.tm.LP_CIndexedTsetlinMachine

pyTsetlinMachine.tm.mc_ctm_pointer

alias of pyTsetlinMachine.tm.LP_CMultiClassConvolutionalTsetlinMachine

pyTsetlinMachine.tools module

class pyTsetlinMachine.tools.Binarizer(max_bits_per_feature=25)

Bases: object

fit(X)

transform(X)

Module contents