check the function

the input is the TEST matrix

function [lower, upper, bound,accuracy] = roughset(Test, Observation, B_indesernible)

% input:

% Test: is an MxN matrix containing the data

% Observation: is the classification of each row in the Test

% B-indesernible: is the target set.

Finally, I found it

http://www.codeforge.com/article/222323

Salam alikoum, Ahmed Hamed

Could you please share the  code I couldn't download it,

Thanks in advance.

salam alikoum

can you send me the code I can't download it, please

Could you please share the code I couldn't download it,

Can you please send me the code.

Dear friends, you can find the code in the attachment, it makes use of the positive approximation to find reduct. The main function is the rough_fwred and it calls automatically the rough_lower to compute the positive approximation. Additionally, you can find the roughset code that computes the lower and upper approximation for a given data set. Note that this code only process numeric values and doesn't process string so you may use something like one-to-one transform to process string.

Hope this help

Hello Mr Hamed,thank you for the code I will test it as soon as possible, Thanks for sharing, I thougth that I am the only one interessted on rougt set but since many people are interessted too it is really kind from you to share the source code

Baraka ALLAH fikoum

Many thanks once again

If you need further help in rough set please don't hesitate to contact me, also you can read my paper in rough set titled "maximal limited similarity based rough set model"

Baraka ALLAH fikoum

Ok Mr Hamed, Thank you so much, I really appreciate.

Best regards

Thanks Mr.Hamed i will test that code sure.If i have doubt i will mail u.

 Ahmed Hamed

I used your rough set functions (the main function rough_fwred which call sub function  rough_lower) to extract just relevant features but the resulted matrix  after applying rough_fwred  reduce the accuracy of image classification. what I did is right and a any advice how to apply rough set to extract just relevant features to improve the percentage of image classification.

thanks

thanks too much for your help 

but  i need from you an example to know how to enter the data

thanks

check the function

the input is the TEST matrix

function [lower, upper, bound,accuracy] = roughset(Test, Observation, B_indesernible)

% input:

% Test: is an MxN matrix containing the data

% Observation: is the classification of each row in the Test

% B-indesernible: is the target set.

Dear  Djanahana Djanahana 

please help me in case of i have the attached  file show the table 

what are 

% Test: is an MxN matrix containing the data

% Observation: is the classification of each row in the Test

% B-indesernible: is the target set.

please write for me the input form please 

thanks

Dear Shaaban Shaaban ·

the test are the set of features (attributes) "a,b,c,d,e,.....,m"

Observation is the column "Decision Level"

B-indesernible: will be either L or M or H

Dear    Dr/ ahmed

thank you very much for your response

my email is   [email protected]

pleas can you send me your email 

thanks

[email protected]

Dear All,

You may use below link to have optimum minimal attribute reduct sets and relevant exhaustive rules.

www.redtoolkit.com

Best regards,

Masoud

For Matlab Code, Visit link

http://dg-algorithm.blogspot.com/