Bugfix in cmvfts
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75e69a1ae1
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ef71a86a7f
pyFTS
@ -345,7 +345,10 @@ def get_point_statistics(data, model, **kwargs):
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if not isinstance(forecasts, (list, np.ndarray)):
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if not isinstance(forecasts, (list, np.ndarray)):
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forecasts = [forecasts]
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forecasts = [forecasts]
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if len(forecasts) != len(ndata) - model.max_lag:
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forecasts = np.array(forecasts[:-1])
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forecasts = np.array(forecasts[:-1])
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else:
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forecasts = np.array(forecasts)
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ret.append(np.round(rmse(ndata[model.max_lag:], forecasts), 2))
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ret.append(np.round(rmse(ndata[model.max_lag:], forecasts), 2))
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ret.append(np.round(mape(ndata[model.max_lag:], forecasts), 2))
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ret.append(np.round(mape(ndata[model.max_lag:], forecasts), 2))
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@ -175,7 +175,7 @@ class HighOrderFTS(fts.FTS):
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for flrg in flrgs:
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for flrg in flrgs:
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if flrg.get_key() not in self.flrgs:
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if flrg.get_key() not in self.flrgs:
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self.flrgs[flrg.get_key()] = flrg;
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self.flrgs[flrg.get_key()] = flrg
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for st in rhs:
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for st in rhs:
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self.flrgs[flrg.get_key()].append_rhs(st)
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self.flrgs[flrg.get_key()].append_rhs(st)
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@ -19,7 +19,7 @@ class ClusteredMVFTS(mvfts.MVFTS):
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self.cluster = None
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self.cluster = None
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"""The most recent trained clusterer"""
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"""The most recent trained clusterer"""
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self.fts_method = kwargs.get('fts_method', hofts.HighOrderFTS)
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self.fts_method = kwargs.get('fts_method', hofts.WeightedHighOrderFTS)
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"""The FTS method to be called when a new model is build"""
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"""The FTS method to be called when a new model is build"""
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self.fts_params = kwargs.get('fts_params', {})
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self.fts_params = kwargs.get('fts_params', {})
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"""The FTS method specific parameters"""
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"""The FTS method specific parameters"""
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@ -31,6 +31,8 @@ model.fit(dataset) #[22, 22, 23, 23, 24])
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print(model)
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print(model)
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Measures.get_point_statistics(dataset, model)
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'''
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'''
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#dataset = SP500.get_data()[11500:16000]
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#dataset = SP500.get_data()[11500:16000]
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#dataset = NASDAQ.get_data()
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#dataset = NASDAQ.get_data()
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@ -100,7 +100,7 @@ model1.append_variable(vprice)
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model1.target_variable = vprice
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model1.target_variable = vprice
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model1.fit(train_mv)
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model1.fit(train_mv)
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#print(model1)
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print(model1)
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print(Measures.get_point_statistics(test_mv, model1))
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print(Measures.get_point_statistics(test_mv, model1))
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#"""
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#"""
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