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python - 如何修复此分类报告警告？

问题描述

我为多类分类创建了一个模型。一切顺利，验证准确率为 84%，但当我打印分类报告时，我收到了以下警告：

 UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
  _warn_prf(average, modifier, msg_start, len(result))

分类报告：

              precision    recall  f1-score   support

           0       0.84      1.00      0.91     51890
           1       0.67      0.04      0.08      8706
           2       0.00      0.00      0.00      1605

    accuracy                           0.84     62201
   macro avg       0.50      0.35      0.33     62201
weighted avg       0.79      0.84      0.77     62201

源代码 -

import pandas as pd

df=pd.read_csv('Crop_Agriculture_Data_2.csv')
df=df.drop('ID',axis=1)

dummies=pd.get_dummies(df[['Crop_Type', 'Soil_Type', 'Pesticide_Use_Category', 'Season']],drop_first=True)
df=df.drop(['Crop_Type', 'Soil_Type', 'Pesticide_Use_Category', 'Season'],axis=1)
df=pd.concat([df,dummies],axis=1)

df['Crop_Damage']=df['Crop_Damage'].map({'Minimal Damage':0,'Partial Damage':1,'Significant Damage':2})

x=df.drop('Crop_Damage',axis=1).values
y=df.Crop_Damage.values
from sklearn.model_selection import train_test_split
x_train,x_test,y_train,y_test=train_test_split(x,y,train_size=0.3,random_state=101)

from sklearn.preprocessing import MinMaxScaler
mms=MinMaxScaler()
x_train=mms.fit_transform(x_train)
x_test=mms.transform(x_test)

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense,Dropout,Flatten

model=Sequential()
model.add(Flatten())
model.add(Dense(10,activation='relu'))
model.add(Dropout(0.3))
model.add(Dense(6,activation='relu'))
model.add(Dropout(0.3))
model.add(Dense(3,activation='softmax'))

model.compile(loss='sparse_categorical_crossentropy',optimizer='adam',metrics=['accuracy'])
model.fit(x_train,y_train,validation_data=(x_test,y_test),epochs=13)

import numpy as np
pred=np.argmax(model.predict(x_test),axis=-1)

from sklearn.metrics import classification_report
print(classification_report(y_test,pred))

我认为这可能是因为大多数数据都属于一个类别，但我不确定。我能做些什么来解决这个问题吗？

标签： pythonmachine-learningscikit-learn

解决方案

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