Remove unused imports from ML pipeline scripts.
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6507b053c5
commit
78b6e7fa07
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@ -15,15 +15,12 @@
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# %% jupyter={"source_hidden": true}
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# %% jupyter={"source_hidden": true}
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# %matplotlib inline
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# %matplotlib inline
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import datetime
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import importlib
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import os
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import os
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import sys
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import sys
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import numpy as np
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import pandas as pd
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import pandas as pd
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import seaborn as sns
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from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
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from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
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from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
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from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
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@ -39,9 +36,6 @@ nb_dir = os.path.split(os.getcwd())[0]
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if nb_dir not in sys.path:
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if nb_dir not in sys.path:
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sys.path.append(nb_dir)
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sys.path.append(nb_dir)
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import machine_learning.labels
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import machine_learning.model
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# %% [markdown]
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# %% [markdown]
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# # RAPIDS models
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# # RAPIDS models
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@ -15,8 +15,6 @@
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# %% jupyter={"source_hidden": true}
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# %% jupyter={"source_hidden": true}
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# %matplotlib inline
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# %matplotlib inline
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import datetime
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import importlib
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import os
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import os
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import sys
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import sys
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@ -29,10 +27,6 @@ from scipy import stats
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from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
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from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
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from sklearn.impute import SimpleImputer
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from sklearn.impute import SimpleImputer
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from sklearn.dummy import DummyClassifier
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from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
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from lightgbm import LGBMClassifier
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import xgboost as xg
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from sklearn.cluster import KMeans
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from sklearn.cluster import KMeans
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@ -43,8 +37,6 @@ nb_dir = os.path.split(os.getcwd())[0]
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if nb_dir not in sys.path:
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if nb_dir not in sys.path:
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sys.path.append(nb_dir)
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sys.path.append(nb_dir)
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import machine_learning.labels
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import machine_learning.model
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from machine_learning.classification_models import ClassificationModels
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from machine_learning.classification_models import ClassificationModels
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# %% [markdown]
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# %% [markdown]
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@ -15,26 +15,18 @@
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# %% jupyter={"source_hidden": true}
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# %% jupyter={"source_hidden": true}
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# %matplotlib inline
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# %matplotlib inline
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import datetime
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import importlib
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import os
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import os
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import sys
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import sys
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import numpy as np
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import pandas as pd
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import pandas as pd
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import seaborn as sns
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from scipy import stats
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from scipy import stats
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from sklearn.model_selection import LeaveOneGroupOut, cross_validate, train_test_split
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from sklearn.model_selection import train_test_split
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from sklearn.impute import SimpleImputer
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from sklearn.impute import SimpleImputer
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from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
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from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
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from sklearn.dummy import DummyClassifier
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from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
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from lightgbm import LGBMClassifier
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import xgboost as xg
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from sklearn.cluster import KMeans
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from sklearn.cluster import KMeans
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from IPython.core.interactiveshell import InteractiveShell
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from IPython.core.interactiveshell import InteractiveShell
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@ -44,8 +36,6 @@ nb_dir = os.path.split(os.getcwd())[0]
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if nb_dir not in sys.path:
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if nb_dir not in sys.path:
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sys.path.append(nb_dir)
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sys.path.append(nb_dir)
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import machine_learning.labels
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import machine_learning.model
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from machine_learning.classification_models import ClassificationModels
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from machine_learning.classification_models import ClassificationModels
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# %% [markdown]
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# %% [markdown]
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