This is Naive Bayes. You can use a program like Weka to accomplish this.

Dear Abdelrahiem Ahmed Hashem,

I suggest you to use the scikit-learn package provided by Python (see link below). It is very easy to use and provides a NaiveBayes object that implement Naive Bayes methods. Naive Bayes methods are a set of supervised learning algorithms based on applying Bayes’ rule with the "naive” assumption of independence between every pair of features. If you want to classify the data into two classes, Naive Bayes is perfect for your purpose.

At the second link you find a tutorial on scikit-learn, and at the third link you find a video series to learn machine learning with Python (including Naive Bayes).

Best regards,

Luca

http://scikit-learn.org/stable/modules/naive_bayes.html

http://scikit-learn.org/stable/tutorial/basic/tutorial.html

http://www.dataschool.io/machine-learning-with-scikit-learn/

Dear Abdelrahiem Ahmed Hashem,

You may use MATLAB tool for Naive Bayes classifier. You use this function to develop classifiers using Naive Bayes:

X Training feature data, Y: Training target data, X': Testing data.

O1 = NaiveBayes.fit(X,Y);

ypre= O1.predict(X');

But before applying this equation, you should remove the feature which have within-class variance is zero or negative. You may refer this paper:

https://www.researchgate.net/publication/303011477_Quality_Assessment_of_Web_Services_Using_Multivariate_Adaptive_Regression_Splines

Conference Paper Quality Assessment of Web Services Using Multivariate Adapti...

Thank you Mr. Lov Kumar, if I need to separate the pixels of an image with this previous rule, how can I set a training data?