I have image datasets divided into 2 Classes (Female/Male) each class located in separate folder . So I have 2 different folders. I used 10 different modules to classify them , for each module I am using 3 different algorithms , and I am doing loop for top-n values ..
and I checked the accuracy across them.
I have matlab code, currently I am doing below steps "manually"
1. I manually separate the images located in the folders (2 classes) as 'Training' and 'Testing' 90:10
2. The code is running across 10 different modules , every time I run the code, I manually change the the module name then run the code to check the result.
3. I manually change the maximum loop number (Top-n)
4. I manually check the accuracy result and fill it into excel sheet.
I need to modify the code to be automated and satisfy those points:
1. Using Cross k Validation (instead of manually separate the data into training and testing sets)
2. Write a loop for those 10 Modules, so Automatically read the module name and generate the result across it (instead of changing the module name manually every time I run the code)
3. Automatically Check the accuracy across those 10 different modules with different top-N values and write it into excel sheet
4. At the end of the program , Save the results as excel containing those date :
* Module Name
* Cross k Number
* Top-N value
the budget is FIXED = 50$ and I need this to be done by today.
12 freelancer đang chào giá trung bình $155 cho công việc này
Hello, dear friend I am expert in matlab. I have a lot of experiences in many projects. I will do your task definitely. Please share your project. Best regards.
Hello Sir. Hope you are doing well. I have worked on different training models for separating training and testing images. I can do all your work. Further we can discuss on chat