Why the accuracy is 100%

■ Overview

Use the "Export Model" function to reproduce the learning process in the classification learner app

Export the classifier and use the "dataset" used in the learning of the classification learner app

I gave it as Input to the exported model, but the result was not different from the correct label.

Is this overfitting and results like this?

* The same result was obtained with the compact model.

■ Questions

Why is the result no different from the correct label?

■ Procedure

① Learn with the classification learner app

② Export the model (ensemble bagging tree)

③ Give the "data set" used in the classification learner application to the export model again.

④ Get output

[KSSV]

On what context these questions are? HAve you trained any model and you got these question? Or these are the questions related to your Home Work? We cannot comment anything on that unless the real problem is known.

[YM]

Hello,KSSV Thank you for your comment.

On what context these questions are?

→I want to reproduce the learning process performed by the classification learner application and analyze the output result to improve the accuracy of the model.

Therefore, when the data set used for training was given to the exported model as input data and the output result was compared with the correct label, there was no error (accuracy on the app is 95%).

I thought I could detect a 5% error, but I'm in trouble.

HAve you trained any model and you got these question?

Or these are the questions related to your Home Work?

→I have trained a model.

I'm not working from home, but I'm currently studying machine learning.

[KSSV]

What model you have trained? What data it is? After attaining 95% accuracy in training, after exporting the model you are not able to get the same/ good prediction accuracy for a new set of data?