Why i get 100% accuracy using CVPartion and SVM
5 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
nurin noor
le 17 Juin 2021
Commenté : nurin noor
le 24 Juin 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
0 commentaires
Réponse acceptée
Asvin Kumar
le 24 Juin 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 commentaires
Asvin Kumar
le 24 Juin 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.
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Classification dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!