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nonzeroexit/AMP-Classifier
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AMP-Classifier2
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AMP-Classifier2
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nonzeroexit
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.gitattributes
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Comb1_aac_ctd_RFE_selected_features_model (1).keras
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Comb1_aac_ctd_RFE_selected_features_model.keras
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Comb1_aac_ctd_RFE_selected_features_scaler.joblib
pickle
Detected Pickle imports (5)
"numpy.ndarray"
,
"numpy._core.multiarray.scalar"
,
"sklearn.preprocessing._data.StandardScaler"
,
"numpy.dtype"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
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Dockerfile
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README.md
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RF.joblib
pickle
Detected Pickle imports (7)
"sklearn.ensemble._forest.RandomForestClassifier"
,
"_codecs.encode"
,
"numpy.dtype"
,
"numpy.ndarray"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.tree._classes.DecisionTreeClassifier"
,
"numpy.core.multiarray._reconstruct"
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SVM.joblib
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Detected Pickle imports (6)
"numpy.dtype"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.svm._classes.SVC"
,
"_codecs.encode"
,
"numpy.ndarray"
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app.py
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arg_scaler.pkl
pickle
Detected Pickle imports (5)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.preprocessing._data.StandardScaler"
,
"numpy.ndarray"
,
"numpy._core.multiarray.scalar"
,
"numpy.dtype"
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arg_xgboost_model.pkl
pickle
Detected Pickle imports (3)
"xgboost.core.Booster"
,
"builtins.bytearray"
,
"xgboost.sklearn.XGBRegressor"
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358 kB
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aur_scaler.pkl
pickle
Detected Pickle imports (5)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.preprocessing._data.StandardScaler"
,
"numpy.ndarray"
,
"numpy._core.multiarray.scalar"
,
"numpy.dtype"
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aur_xgboost_model.pkl
pickle
Detected Pickle imports (3)
"xgboost.core.Booster"
,
"builtins.bytearray"
,
"xgboost.sklearn.XGBRegressor"
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coli_scaler.pkl
pickle
Detected Pickle imports (5)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.preprocessing._data.StandardScaler"
,
"numpy.ndarray"
,
"numpy._core.multiarray.scalar"
,
"numpy.dtype"
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coli_xgboost_model.pkl
pickle
Detected Pickle imports (3)
"xgboost.core.Booster"
,
"builtins.bytearray"
,
"xgboost.sklearn.XGBRegressor"
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382 kB
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mic_worker.py
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norm (1).joblib
pickle
Detected Pickle imports (6)
"sklearn.preprocessing._data.MinMaxScaler"
,
"numpy.ndarray"
,
"_codecs.encode"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.dtype"
,
"numpy.core.multiarray._reconstruct"
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norm (2).joblib
pickle
Detected Pickle imports (6)
"sklearn.preprocessing._data.MinMaxScaler"
,
"numpy.ndarray"
,
"_codecs.encode"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.dtype"
,
"numpy.core.multiarray._reconstruct"
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norm (4).joblib
pickle
Detected Pickle imports (6)
"sklearn.preprocessing._data.MinMaxScaler"
,
"numpy.ndarray"
,
"_codecs.encode"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.dtype"
,
"numpy.core.multiarray._reconstruct"
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norm.joblib
pickle
Detected Pickle imports (6)
"_codecs.encode"
,
"numpy.core.multiarray._reconstruct"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.preprocessing._data.MinMaxScaler"
,
"numpy.ndarray"
,
"numpy.dtype"
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22.1 kB
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pne_mlp_model.pkl
pickle
Detected Pickle imports (7)
"numpy.random._mt19937.MT19937"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.neural_network._multilayer_perceptron.MLPRegressor"
,
"numpy.random._pickle.__randomstate_ctor"
,
"numpy.ndarray"
,
"numpy.random._pickle.__bit_generator_ctor"
,
"numpy.dtype"
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pne_pca.pkl
pickle
Detected Pickle imports (4)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.decomposition._pca.PCA"
,
"numpy.ndarray"
,
"numpy.dtype"
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338 kB
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pne_scaler.pkl
pickle
Detected Pickle imports (5)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.preprocessing._data.StandardScaler"
,
"numpy.ndarray"
,
"numpy._core.multiarray.scalar"
,
"numpy.dtype"
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25.2 kB
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requirements.txt
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