我不知道如何解決這個問題，有人能給我解釋一下嗎？我正在努力通過更改 DecisionTreeClassifier 的參數(shù)來在循環(huán)中獲得最佳 precision_scoreimport pandas as pdfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.metrics import precision_scorefrom sklearn.model_selection import train_test_split df = pd.read_csv('songs.csv') X = df.drop(['song','artist','genre','lyrics'],axis=1) y = df.artist X_train,X_test,y_train,y_test = train_test_split(X,y) scores_data = pd.DataFrame() for depth in range(1,100): clf = DecisionTreeClassifier(max_depth=depth,criterion='entropy').fit(X_train,y_train) train_score = clf.score(X_train,y_train) test_score = clf.score(X_test,y_test) preds = clf.predict(X_test) precision_score = precision_score(y_test,preds,average='micro') temp_scores = pd.DataFrame({'depth':[depth], 'test_score':[test_score], 'train_score':[train_score], 'precision_score:':[precision_score]}) scores_data = scores_data.append(temp_scores) 這是我的錯誤：---------------------------------------------------------------------------TypeError Traceback (most recent call last)<ipython-input-50-f4a4eaa48ce6> in <module> 17 test_score = clf.score(X_test,y_test) 18 preds = clf.predict(X_test)---> 19 precision_score = precision_score(y_test,preds,average='micro') 20 21 temp_scores = pd.DataFrame({'depth':[depth],**TypeError: 'numpy.float64' object is not callable**這是數(shù)據(jù)集https://i.stack.imgur.com/QJXSY.png
1 回答
MMTTMM
TA貢獻1869條經(jīng)驗 獲得超4個贊
循環(huán)中的最后一行：
precision_score = precision_score(y_test,preds,average='micro')
temp_scores = pd.DataFrame({'depth':[depth],
'test_score':[test_score],
'train_score':[train_score],
'precision_score:':[precision_score]})
scores_data = scores_data.append(temp_scores)
應改為：
precision_score_ = precision_score(y_test,preds,average='micro')
temp_scores = pd.DataFrame({'depth':[depth],
'test_score':[test_score],
'train_score':[train_score],
'precision_score:':[precision_score_]})
scores_data = scores_data.append(temp_scores)
您定義precision_score為 numpy 數(shù)組，然后像函數(shù)一樣調(diào)用它（下一個周期）。
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