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구글 코랩에서 실행하기\n"," | \n"," 구글 코랩에서 실행하기\n"," | \n","
| \n"," | alcohol | \n","sugar | \n","pH | \n","class | \n","
|---|---|---|---|---|
| 0 | \n","9.4 | \n","1.9 | \n","3.51 | \n","0.0 | \n","
| 1 | \n","9.8 | \n","2.6 | \n","3.20 | \n","0.0 | \n","
| 2 | \n","9.8 | \n","2.3 | \n","3.26 | \n","0.0 | \n","
| 3 | \n","9.8 | \n","1.9 | \n","3.16 | \n","0.0 | \n","
| 4 | \n","9.4 | \n","1.9 | \n","3.51 | \n","0.0 | \n","
| \n"," | alcohol | \n","sugar | \n","pH | \n","class | \n","
|---|---|---|---|---|
| count | \n","6497.000000 | \n","6497.000000 | \n","6497.000000 | \n","6497.000000 | \n","
| mean | \n","10.491801 | \n","5.443235 | \n","3.218501 | \n","0.753886 | \n","
| std | \n","1.192712 | \n","4.757804 | \n","0.160787 | \n","0.430779 | \n","
| min | \n","8.000000 | \n","0.600000 | \n","2.720000 | \n","0.000000 | \n","
| 25% | \n","9.500000 | \n","1.800000 | \n","3.110000 | \n","1.000000 | \n","
| 50% | \n","10.300000 | \n","3.000000 | \n","3.210000 | \n","1.000000 | \n","
| 75% | \n","11.300000 | \n","8.100000 | \n","3.320000 | \n","1.000000 | \n","
| max | \n","14.900000 | \n","65.800000 | \n","4.010000 | \n","1.000000 | \n","
| \n"," 구글 코랩에서 실행하기\n"," | \n","
GridSearchCV(estimator=DecisionTreeClassifier(random_state=42), n_jobs=-1,\n"," param_grid={'min_impurity_decrease': [0.0001, 0.0002, 0.0003,\n"," 0.0004, 0.0005]})In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. GridSearchCV(estimator=DecisionTreeClassifier(random_state=42), n_jobs=-1,\n"," param_grid={'min_impurity_decrease': [0.0001, 0.0002, 0.0003,\n"," 0.0004, 0.0005]})DecisionTreeClassifier(min_impurity_decrease=0.0001, random_state=42)
DecisionTreeClassifier(min_impurity_decrease=0.0001, random_state=42)
GridSearchCV(estimator=DecisionTreeClassifier(random_state=42), n_jobs=-1,\n"," param_grid={'max_depth': range(5, 20),\n"," 'min_impurity_decrease': array([0.0001, 0.0002, 0.0003, 0.0004, 0.0005, 0.0006, 0.0007, 0.0008,\n"," 0.0009]),\n"," 'min_samples_split': range(2, 100, 10)})In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. GridSearchCV(estimator=DecisionTreeClassifier(random_state=42), n_jobs=-1,\n"," param_grid={'max_depth': range(5, 20),\n"," 'min_impurity_decrease': array([0.0001, 0.0002, 0.0003, 0.0004, 0.0005, 0.0006, 0.0007, 0.0008,\n"," 0.0009]),\n"," 'min_samples_split': range(2, 100, 10)})DecisionTreeClassifier(max_depth=14, min_impurity_decrease=0.0004,\n"," min_samples_split=12, random_state=42)
DecisionTreeClassifier(max_depth=14, min_impurity_decrease=0.0004,\n"," min_samples_split=12, random_state=42)
RandomizedSearchCV(estimator=DecisionTreeClassifier(random_state=42),\n"," n_iter=100, n_jobs=-1,\n"," param_distributions={'max_depth': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225466d40>,\n"," 'min_impurity_decrease': <scipy.stats._distn_infrastructure.rv_continuous_frozen object at 0x7e5225464b50>,\n"," 'min_samples_leaf': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e52254661d0>,\n"," 'min_samples_split': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225467c10>},\n"," random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. RandomizedSearchCV(estimator=DecisionTreeClassifier(random_state=42),\n"," n_iter=100, n_jobs=-1,\n"," param_distributions={'max_depth': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225466d40>,\n"," 'min_impurity_decrease': <scipy.stats._distn_infrastructure.rv_continuous_frozen object at 0x7e5225464b50>,\n"," 'min_samples_leaf': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e52254661d0>,\n"," 'min_samples_split': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225467c10>},\n"," random_state=42)DecisionTreeClassifier(max_depth=39,\n"," min_impurity_decrease=0.00034102546602601173,\n"," min_samples_leaf=7, min_samples_split=13,\n"," random_state=42)
DecisionTreeClassifier(max_depth=39,\n"," min_impurity_decrease=0.00034102546602601173,\n"," min_samples_leaf=7, min_samples_split=13,\n"," random_state=42)
RandomizedSearchCV(estimator=DecisionTreeClassifier(random_state=42,\n"," splitter='random'),\n"," n_iter=100, n_jobs=-1,\n"," param_distributions={'max_depth': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225466d40>,\n"," 'min_impurity_decrease': <scipy.stats._distn_infrastructure.rv_continuous_frozen object at 0x7e5225464b50>,\n"," 'min_samples_leaf': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e52254661d0>,\n"," 'min_samples_split': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225467c10>},\n"," random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. RandomizedSearchCV(estimator=DecisionTreeClassifier(random_state=42,\n"," splitter='random'),\n"," n_iter=100, n_jobs=-1,\n"," param_distributions={'max_depth': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225466d40>,\n"," 'min_impurity_decrease': <scipy.stats._distn_infrastructure.rv_continuous_frozen object at 0x7e5225464b50>,\n"," 'min_samples_leaf': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e52254661d0>,\n"," 'min_samples_split': <scipy.stats._distn_infrastructure.rv_discrete_frozen object at 0x7e5225467c10>},\n"," random_state=42)DecisionTreeClassifier(max_depth=43,\n"," min_impurity_decrease=0.00011407982271508446,\n"," min_samples_leaf=19, min_samples_split=18,\n"," random_state=42, splitter='random')
DecisionTreeClassifier(max_depth=43,\n"," min_impurity_decrease=0.00011407982271508446,\n"," min_samples_leaf=19, min_samples_split=18,\n"," random_state=42, splitter='random')
| \n"," 구글 코랩에서 실행하기\n"," | \n","