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Remove unused imports from ML pipeline scripts.

ml_pipeline
Primoz 2022-12-09 13:53:16 +01:00
parent 6507b053c5
commit 78b6e7fa07
3 changed files with 1 additions and 25 deletions
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6
exploration/ml_pipeline_classification.py
View File

@ -15,15 +15,12 @@
# %% jupyter={"source_hidden": true}
# %matplotlib inline
import datetime
import importlib
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
@ -39,9 +36,6 @@ nb_dir = os.path.split(os.getcwd())[0]
if nb_dir not in sys.path:
sys.path.append(nb_dir)
import machine_learning.labels
import machine_learning.model
# %% [markdown]
# # RAPIDS models

8
exploration/ml_pipeline_classification_with_clustering.py
View File

@ -15,8 +15,6 @@
# %% jupyter={"source_hidden": true}
# %matplotlib inline
import datetime
import importlib
import os
import sys
@ -29,10 +27,6 @@ from scipy import stats
from sklearn.model_selection import LeaveOneGroupOut, cross_validate, StratifiedKFold
from sklearn.impute import SimpleImputer
from sklearn.dummy import DummyClassifier
from sklearn import linear_model, svm, naive_bayes, neighbors, tree, ensemble
from lightgbm import LGBMClassifier
import xgboost as xg
from sklearn.cluster import KMeans
@ -43,8 +37,6 @@ nb_dir = os.path.split(os.getcwd())[0]
if nb_dir not in sys.path:
sys.path.append(nb_dir)
import machine_learning.labels
import machine_learning.model
from machine_learning.classification_models import ClassificationModels
# %% [markdown]

12
exploration/ml_pipeline_classification_with_clustering_2_class.py
View File

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