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)