Why i get 100% accuracy using CVPartion and SVM
2 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
nurin noor
am 17 Jun. 2021
Kommentiert: nurin noor
am 24 Jun. 2021
Hi everyone, i am new to machine learning. I am trying to classify "model1". I used cv partition with 70% of test and 30% of training. However, i am getting 100% accuracy. i am afraid i am using the same data to test and train but i thought cvpartition would help to seperate the data, right? Or i am using the same data for train and testing? Here is my code. I was referring the code from here
https://www.mathworks.com/matlabcentral/answers/377839-split-training-data-and-testing-data
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/656965/image.jpeg)
0 Kommentare
Akzeptierte Antwort
Asvin Kumar
am 24 Jun. 2021
Your usage of cvpartition is correct. You are not using the same data for training and testing.
Your SVM jusr seems to be working very well.
3 Kommentare
Asvin Kumar
am 24 Jun. 2021
Yes, that's what I meant. Everything should be working fine as your cvparition is correct. Data test and training are different.
Why the accuracy is 100% depends on the specific problem that you are trying to solve. SVMs just might be well suited for your data.
Weitere Antworten (0)
Siehe auch
Kategorien
Mehr zu Classification finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!