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