def train(self, ndata, **kwargs): tmpdata = FuzzySet.fuzzyfy(ndata, partitioner=self.partitioner, method='maximum', mode='sets') flrs = FLR.generate_recurrent_flrs(tmpdata) self.generate_FLRG(flrs)
def train(self, data, **kwargs): if self.method == 'unconditional': window_size = kwargs.get('parameters', 1) tmpdata = common.fuzzySeries(data, self.partitioner.sets, self.partitioner.ordered_sets, window_size, method='fuzzy') else: tmpdata = common.fuzzySeries(data, self.partitioner.sets, self.partitioner.ordered_sets, method='fuzzy', const_t=0) flrs = FLR.generate_recurrent_flrs(tmpdata) self.generate_flrg(flrs) if self.method == 'conditional': self.forecasts = self.forecast(data, no_update=True) self.residuals = np.array(data[1:]) - np.array(self.forecasts[:-1]) self.variance_residual = np.var(self.residuals) # np.max(self.residuals self.mean_residual = np.mean(self.residuals) self.residuals = self.residuals[-self.memory_window:].tolist() self.forecasts = self.forecasts[-self.memory_window:] self.inputs = np.array(data[-self.memory_window:]).tolist()
def train(self, data, **kwargs): parameters = kwargs.get('parameters', 'fuzzy') if parameters == 'monotonic': tmpdata = FuzzySet.fuzzyfy_series_old(data, self.sets) flrs = FLR.generate_recurrent_flrs(tmpdata) self.generateFLRG(flrs) else: self.generate_flrg(data)
def train(self, data, **kwargs): window_size = kwargs.get('parameters', 1) tmpdata = common.fuzzySeries(data, self.sets, self.partitioner.ordered_sets, window_size, method='fuzzy') flrs = FLR.generate_recurrent_flrs(tmpdata) self.generate_flrg(flrs)
def train(self, data, **kwargs): self.configure_lags(**kwargs) parameters = kwargs.get('parameters','fuzzy') if parameters == 'monotonic': tmpdata = self.partitioner.fuzzyfy(data, mode='sets', method='maximum') flrs = FLR.generate_recurrent_flrs(tmpdata) self.generate_flrg(flrs) else: self.generate_flrg(data)
def train(self, data, **kwargs): if kwargs.get('sets', None) is not None: self.sets = kwargs.get('sets', None) tmpdata = FuzzySet.fuzzyfy_series_old(data, self.sets) flrs = FLR.generate_recurrent_flrs(tmpdata) self.generate_flrg(flrs)
def train(self, data, **kwargs): tmpdata = self.partitioner.fuzzyfy(data, method='maximum', mode='sets') flrs = FLR.generate_recurrent_flrs(tmpdata) self.generate_flrg(flrs, self.c)
def train(self, ndata, **kwargs): tmpdata = FuzzySet.fuzzyfy_series(ndata, self.sets, method='maximum') flrs = FLR.generate_recurrent_flrs(tmpdata) self.generate_flrg(flrs)