Bugfixes due to circular imports
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@ -2,9 +2,8 @@
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Kohonen Self Organizing Maps for Fuzzy Time Series
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"""
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import pandas as pd
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from pyFTS.models.multivariate import wmvfts
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#from pyFTS.models.multivariate import wmvfts
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from typing import Tuple
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from pyFTS.common.Transformations import Transformation
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from typing import List
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from pyFTS.common.transformations.transformation import Transformation
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@ -12,7 +12,7 @@ import pandas as pd
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from pyFTS.partitioners import Grid #, Entropy, Util as pUtil, Simple
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#from pyFTS.benchmarks import benchmarks as bchmk, Measures
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#from pyFTS.models import chen, yu, cheng, ismailefendi, hofts, pwfts, tsaur, song, sadaei, ifts
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from pyFTS.models import pwfts, hofts, chen
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from pyFTS.models import pwfts, hofts
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#from pyFTS.models.ensemble import ensemble
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from pyFTS.common import Transformations, Membership, Util
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#from pyFTS.benchmarks import arima, quantreg #BSTS, gaussianproc, knn
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@ -38,8 +38,8 @@ l = len(dados)
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particionador = Grid.GridPartitioner(data = dados, npart = 10, func = Membership.trimf)
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#modelo = pwfts.ProbabilisticWeightedFTS(partitioner = particionador, order = 1)
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modelo = hofts.WeightedHighOrderFTS(partitioner = particionador, order = 1, standard_horizon=1, lags=[2])
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modelo = pwfts.ProbabilisticWeightedFTS(partitioner = particionador, order = 1)
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#modelo = hofts.WeightedHighOrderFTS(partitioner = particionador, order = 1, standard_horizon=1, lags=[2])
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#modelo = chen.ConventionalFTS(partitioner = particionador, standard_horizon=3)
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modelo.fit(dados)
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