Why i get 100% accuracy using CVPartion and SVM

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

Answer 1

[Asvin Kumar]

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.

[nurin noor]

Did you mean everything should be working fine as my cvparition is correct, data test and training are different? It is kinda weird as accuracy is 100%. Or it is not weird? Sorry, Im new to machine learning.

[Asvin Kumar]

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.

[nurin noor]

i see. very much understood. it is such a relief to know my SVM implementation is correct. Thank you so much !!