def eval(self, data, k_fold=1):
Likelihood = []
for i in range(len(data.getData(self.viewPoints[0])) // k_fold):
# We initialize the models
self.LTM = []
for viewPoint in self.viewPoints:
self.LTM.append(
longTermModel.longTermModel(viewPoint,
maxOrder=self.maxOrder))
# We train them with the given dataset
k = 0
for viewPoint in self.viewPoints:
self.LTM[k].train(
data.getData(viewPoint)[:i * k_fold] +
data.getData(viewPoint)[(i + 1) * k_fold:])
print(data.getData(viewPoint))
print()
print(
data.getData(viewPoint)[:i * k_fold] +
data.getData(viewPoint)[(i + 1) * k_fold:])
quit()
k += 1
def train(self, data):
"""
Train the models from data
:param data: data to train from
:type data: data object
"""
k = 0
for viewPoint in self.viewPoints:
self.LTM[k].train(data.getData(viewPoint))
k += 1
def train(self, data, preComputeEntropies=False):
"""
Train the models from data
:param data: data to train from
:type data: data object
"""
k = 0
for viewPoint in self.viewPoints:
self.LTM[k].train(data.getData(viewPoint),
preComputeEntropies=preComputeEntropies)
k += 1