X = X.reshape((entries, 19, 38))
# Answers
Y = data[:, -1]
split = 0.8
z = math.floor(len(data) * 0.8)
X_train = X[:z]
Y_train = Y[:z]
X_test = X[z:]
Y_test = Y[z:]
epochs = 20
tm = MultiClassConvolutionalTsetlinMachine2D(10000,
7500,
8.0, (19, 19),
weighted_clauses=True)
info = "; ".join(f"""
Clauses: {tm.number_of_clauses}
T: {tm.T}
s: {tm.s}
Epochs: {epochs}
Moves: 250
Games: {data.shape[0]}
""".strip().split("\n"))
total_acc = []
print(info)
print("Starting training")
#import sys
#sys.exit(1)
#------------------------------------------------------------
from pyTsetlinMachine.tm import MultiClassConvolutionalTsetlinMachine2D
print("Setting Up Machine")
clauses = int(variables["Connect4"]["Clause"])
T = variables["Connect4"]["T"]
s = variables["Connect4"]["S"]
epochs = int(variables["Connect4"]["epochs"])
ctm = MultiClassConvolutionalTsetlinMachine2D(1000,
50,
14.617627461915859, (4, 4),
weighted_clauses=True,
boost_true_positive_feedback=0)
ctm.fit(TrainX, TrainY, epochs=15)
print("Accuracy:", 100 * (ctm.predict(TestX) == TestY).mean())
def GetOutput(tm, tm_class, clause):
output = []
for i in range(84 * 2):
outputbit = tm.ta_action(tm_class, clause, i)
output.append(outputbit)
return output