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vavelychko
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nextplase_project
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Joblib
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096e220
nextplase_project
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162 commits
vavelychko
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Model_A.joblib
pickle
Detected Pickle imports (7)
"numpy.ndarray"
,
"numpy.dtype"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"sklearn.ensemble._forest.RandomForestClassifier"
,
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
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Model_A_feature_names.json
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model_1_A.joblib
pickle
Detected Pickle imports (7)
"sklearn.ensemble._forest.RandomForestClassifier"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"numpy.ndarray"
,
"numpy.dtype"
,
"_codecs.encode"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
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model_1_A_feature_names.json
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model_2_1.joblib
pickle
Detected Pickle imports (6)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"numpy.ndarray"
,
"sklearn.ensemble._gb.GradientBoostingRegressor"
,
"numpy.dtype"
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model_2_1_feature_names.json
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model_2_A.joblib
pickle
Detected Pickle imports (7)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.ensemble._forest.RandomForestClassifier"
,
"numpy.ndarray"
,
"numpy.dtype"
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model_2_A_feature_names.json
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model_A.joblib
pickle
Detected Pickle imports (7)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.ensemble._forest.RandomForestClassifier"
,
"numpy.ndarray"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"_codecs.encode"
,
"numpy.dtype"
,
"numpy.core.multiarray._reconstruct"
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model_A_feature_names.json
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model_B_1.joblib
pickle
Detected Pickle imports (7)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.ensemble._forest.RandomForestClassifier"
,
"numpy.ndarray"
,
"numpy.dtype"
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model_B_1_feature_names.json
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model_B_2.joblib
pickle
Detected Pickle imports (7)
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"numpy.ndarray"
,
"numpy.dtype"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"sklearn.ensemble._forest.RandomForestClassifier"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
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model_B_2_feature_names.json
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model_B_3.joblib
pickle
Detected Pickle imports (6)
"_codecs.encode"
,
"numpy.dtype"
,
"numpy.ndarray"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.ensemble._gb.GradientBoostingClassifier"
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model_B_3_feature_names.json
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model_c_5.joblib
158 MB
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model_c_5_feature_names.json
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model_d_5.joblib
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model_d_5_feature_names.json
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model_d_5_scaler.joblib
pickle
Detected Pickle imports (6)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"_codecs.encode"
,
"sklearn.preprocessing._data.MaxAbsScaler"
,
"numpy.ndarray"
,
"numpy._core.multiarray._reconstruct"
,
"numpy.dtype"
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model_e_5_scaler.joblib
pickle
Detected Pickle imports (6)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"_codecs.encode"
,
"sklearn.preprocessing._data.MaxAbsScaler"
,
"numpy.ndarray"
,
"numpy._core.multiarray._reconstruct"
,
"numpy.dtype"
How to fix it?
1.37 kB
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model_ั_5.joblib
pickle
Detected Pickle imports (7)
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.tree._classes.DecisionTreeRegressor"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.ndarray"
,
"numpy.dtype"
,
"sklearn.ensemble._forest.RandomForestRegressor"
How to fix it?
140 MB
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model_ั_5_feature_names.json
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model_ั_5_scaler.joblib
pickle
Detected Pickle imports (6)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.preprocessing._data.MaxAbsScaler"
,
"numpy.ndarray"
,
"numpy.dtype"
How to fix it?
1.54 kB
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optimized_random_forest_model.joblib
pickle
Detected Pickle imports (7)
"numpy.dtype"
,
"numpy.core.multiarray._reconstruct"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.ensemble._forest.RandomForestClassifier"
,
"numpy.ndarray"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"_codecs.encode"
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413 MB
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optimized_random_forest_model_feature_names.json
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