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tkamal
/
ezehome-energy-intelligence
like
0
synthetic-ezehome-2yr
energy-forecasting
time-series
xgboost
lstm
anomaly-detection
smart-home
ezehome
License:
mit
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ezehome-energy-intelligence
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25 commits
tkamal
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.gitattributes
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README.md
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cluster_labels.json
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iforest.pkl
pickle
Detected Pickle imports (6)
"sklearn.tree._tree.Tree"
,
"sklearn.tree._classes.ExtraTreeRegressor"
,
"numpy.dtype"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"sklearn.ensemble._iforest.IsolationForest"
,
"numpy.ndarray"
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kmeans.pkl
pickle
Detected Pickle imports (5)
"numpy.ndarray"
,
"numpy.core.multiarray.scalar"
,
"numpy.dtype"
,
"sklearn.cluster._kmeans.KMeans"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
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lstm.pkl
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pickle
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No problematic imports detected
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260 kB
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model_comparison.csv
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model_comparison_val.csv
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model_metadata.json
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prophet.pkl
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pickle
Detected Pickle imports (8)
"numpy.dtype"
,
"pandas.core.indexes.base.Index"
,
"numpy.ndarray"
,
"pandas.core.indexes.base._new_Index"
,
"pandas.core.series.Series"
,
"prophet.forecaster.Prophet"
,
"pandas.core.internals.managers.SingleBlockManager"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
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1.1 MB
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scaler.pkl
pickle
Detected Pickle imports (4)
"sklearn.preprocessing._data.MinMaxScaler"
,
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.ndarray"
,
"numpy.dtype"
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scaler_cluster.pkl
pickle
Detected Pickle imports (7)
"joblib.numpy_pickle.NumpyArrayWrapper"
,
"numpy.dtype"
,
"numpy.core.multiarray._reconstruct"
,
"numpy.ndarray"
,
"numpy.core.multiarray.scalar"
,
"None.dtype"
,
"sklearn.preprocessing._data.StandardScaler"
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xgboost.pkl
pickle
Detected Pickle imports (3)
"xgboost.core.Booster"
,
"xgboost.sklearn.XGBRegressor"
,
"builtins.bytearray"
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827 kB
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xgboost_enhanced.pkl
pickle
Detected Pickle imports (3)
"xgboost.core.Booster"
,
"xgboost.sklearn.XGBRegressor"
,
"builtins.bytearray"
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