Classify_result=[]
names=[]
prediction=[]
for name,classifier in Classifiers:
classifier=classifier
classifier.fit(x_train,y_train)
#classifier.Imputer().fit_transform(x_train,y_train)
y_pred=classifier.predict(x_test)
recall=recall_score(y_test,y_pred)
precision=precision_score(y_test,y_pred)
f1score = f1_score(y_test, y_pred)
class_eva=pd.DataFrame([recall,precision,f1score])
Classify_result.append(class_eva)
name=pd.Series(name)
names.append(name)
y_pred=pd.Series(y_pred)
prediction.append(y_pred)
开始报的这个错误,按照网上说的方法修改后又报新的错误。
ValueError: Input contains NaN, infinity or a value too large for dtype('float32').
新修改的代码:
Classify_result=[]
names=[]
prediction=[]
for name,classifier in Classifiers:
classifier=classifier
#classifier.fit(x_train,y_train)
classifier.Imputer().fit_transform(x_train,y_train)
y_pred=classifier.predict(x_test)
recall=recall_score(y_test,y_pred)
precision=precision_score(y_test,y_pred)
f1score = f1_score(y_test, y_pred)
class_eva=pd.DataFrame([recall,precision,f1score])
Classify_result.append(class_eva)
name=pd.Series(name)
names.append(name)
y_pred=pd.Series(y_pred)
prediction.append(y_pred)
报的新错误:
AttributeError: 'RandomForestClassifier' object has no attribute 'Imputer'