'how to use LabelEncode.inversetransform from a saved model to predict unseen data
For a multi class classification, I used label encoder to convert the categorical target variable to a numerical variable. got some good accuracy and saved the model to my local drive using joblib module.
So, in the future, if I load the model from my drive and try to predict using model.predict(['laptop not charging']) I will get numerical value as output because I have trained the model using numerical data only.
I know it won't work but mentioning here for reference that even this also won't work
le=LabelEncoder()
print(le.inverse_transform(model.predict(['laptop not charging'])))
I want the output as asset issue. How to get asset issue as a output?
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|