1 | import sklearn.manifold as skl_manifold |
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2 | |||
3 | from Orange.distance import SklDistance, SpearmanDistance, PearsonDistance |
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4 | from Orange.projection import SklProjector |
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5 | |||
6 | __all__ = ["MDS", "Isomap", "LocallyLinearEmbedding"] |
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7 | |||
8 | |||
9 | class MDS(SklProjector): |
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10 | __wraps__ = skl_manifold.MDS |
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11 | name = 'mds' |
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12 | |||
13 | def __init__(self, n_components=2, metric=True, n_init=4, max_iter=300, |
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14 | eps=0.001, n_jobs=1, random_state=None, |
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15 | dissimilarity='euclidean', |
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16 | preprocessors=None): |
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17 | super().__init__(preprocessors=preprocessors) |
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18 | self.params = vars() |
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19 | self._metric = dissimilarity |
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20 | |||
21 | def __call__(self, data): |
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22 | distances = SklDistance, SpearmanDistance, PearsonDistance |
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23 | if isinstance(self._metric, distances): |
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24 | data = self.preprocess(data) |
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25 | X, Y, domain = data.X, data.Y, data.domain |
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26 | dist_matrix = self._metric(X) |
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27 | self.params['dissimilarity'] = 'precomputed' |
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28 | clf = self.fit(dist_matrix, Y=Y) |
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29 | elif self._metric is 'precomputed': |
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30 | dist_matrix, Y, domain = data, None, None |
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31 | clf = self.fit(dist_matrix, Y=Y) |
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32 | else: |
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33 | data = self.preprocess(data) |
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34 | X, Y, domain = data.X, data.Y, data.domain |
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35 | clf = self.fit(X, Y=Y) |
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36 | clf.domain = domain |
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37 | return clf |
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38 | |||
39 | def fit(self, X, init=None, Y=None): |
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40 | proj = self.__wraps__(**self.params) |
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41 | return proj.fit(X, init=init, y=Y) |
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42 | |||
43 | |||
44 | class Isomap(SklProjector): |
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45 | __wraps__ = skl_manifold.Isomap |
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46 | name = 'isomap' |
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47 | |||
48 | def __init__(self, n_neighbors=5, n_components=2, eigen_solver='auto', |
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49 | max_iter=None, path_method='auto', |
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50 | neighbors_algorithm='auto', preprocessors=None): |
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51 | super().__init__(preprocessors=preprocessors) |
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52 | self.params = vars() |
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53 | |||
54 | |||
55 | class LocallyLinearEmbedding(SklProjector): |
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56 | __wraps__ = skl_manifold.LocallyLinearEmbedding |
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57 | name = 'lle' |
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58 | |||
59 | def __init__(self, n_neighbors=5, n_components=2, reg=0.001, |
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60 | eigen_solver='auto', tol=1e-06 , max_iter=100, |
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61 | method='standard', hessian_tol=0.0001, |
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62 | modified_tol=1e-12, neighbors_algorithm='auto', |
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63 | random_state=None, preprocessors=None): |
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64 | super().__init__(preprocessors=preprocessors) |
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65 | self.params = vars() |
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66 |
This can be caused by one of the following:
1. Missing Dependencies
This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands.
2. Missing __init__.py files
This error could also result from missing
__init__.py
files in your module folders. Make sure that you place one file in each sub-folder.