랜덤포레스트 공략
랜덤포레스트는 NULL값을 받아낼수있으며 숫자형데이터만 받아낼수있다 from sklearn.ensemble import RandomForestClassifier rf = RandomForestClassifier(n_estimators=150, max_depth=8, min_samples_leaf=4, max_features=0.2, n_jobs=-1, random_state=0) rf.fit(train.drop(['id', 'target'],axis=1), train.target) features = train.drop(['id', 'target'],axis=1).columns.values print("----- Training Done -----") RandomForestClassifier 모델을 초기..
상관분석 코드
아래코드를 사용하면 상관 분석이 가능하다 colormap = plt.cm.magma plt.figure(figsize=(16,12)) plt.title('Pearson correlation of continuous features', y=1.05, size=15) sns.heatmap(train_float.corr(),linewidths=0.1,vmax=1.0, square=True, cmap=colormap, linecolor='white', annot=True) #train_int = train_int.drop(["id", "target"], axis=1) # colormap = plt.cm.bone # plt.figure(figsize=(21,16)) # plt.title('Pearson corre..