Evaluation

성능 평가 지표(Evaluation Metric)

• 분류 성능 평가 지표
  • 정확도(Accuracy)
  • 오차행렬(Confusion Matrix)
  • 정밀도(Precision)
  • 재현율(Recall)
  • F1 Score
  • ROC AUC

1. 정확도

함수

```python from sklearn import preprocessing def fillna(df): df['Age'].fillna(df['Age'].mean(), inplace = True) df['Cabin'].fillna('N', inplace = True) df['Embarked'].fillna('N', inplace = True) df['Fare'].fillna(0, inplace = True) return df def drop_features(df): df.drop(['PassengerId','Name','Ticket'], axis = 1, inplace = True) return df def format_features(df): df['Cabin'] = df['Cabin'].str[:1] features = ['Cabin','Sex','Embarked'] for feature in features: le = preprocessing.LabelEncoder() le = le.fit(df[feature]) df[feature] = le.transform(df[feature]) return df def transform_features(df): df = fillna(df) df = drop_features(df) df = format_features(df) return df ```