資源簡介
決策樹對于數(shù)據(jù)分類的Python實(shí)現(xiàn),測試集和訓(xùn)練集分別給出,而且數(shù)據(jù)已經(jīng)處理好的,
代碼片段和文件信息
import?os
import?sys
import?logging
import?pandas?as?pd
train_file?=?os.path.join(“data““train.csv“)
test_file?=?os.path.join(“data““test.csv“)
train_df?=?pd.read_csv(train_filesep=““header?=?0quoting?=?3)
X_train=train_df.iloc[:1:]
y_train=train_df.iloc[::1]
test_df=pd.read_csv(test_filesep=‘‘header=0quoting=3)
X_test=test_df.iloc[::]
from?sklearn.ensemble?import?RandomForestClassifier
clf=RandomForestClassifier(n_estimators=100)
clf.fit(X_trainy_train)
y_pred=clf.predict(X_test)
print(y_pred)
with?open(os.path.join(‘random_forest.csv‘)‘w‘)?as?my_file:
my_file.write(‘ImageidLabel\n‘)
for?i?in?range(len(y_pred)):
my_file.write(‘%d%d\n‘%(iy_pred[i]))
print(‘save‘)
?屬性????????????大小?????日期????時(shí)間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2018-05-15?17:31??隨機(jī)森林的應(yīng)用\
?????文件?????????745??2018-04-19?10:42??隨機(jī)森林的應(yīng)用\redom_forest.py
?????文件????51118296??2018-04-12?09:37??隨機(jī)森林的應(yīng)用\test.csv
?????文件????76775041??2018-04-12?09:37??隨機(jī)森林的應(yīng)用\train.csv
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