A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...

1 Computer Science Department, Babcock University, Ilishan-Remo, Ogun State, Nigeria. 2 Computer Science Department, Adeleke University, Ede, Osun State, Nigeria. 3 Department of Applied Mathematics, ...

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...

Abstract: Data mining in the educational field has been commonly used to analyze patterns in academic databases that are hard to analyze manually. The main objective of this paper is to compare the ...

Implemented Preprocessing steps, Feature Extraction techniques and Naive Bayes Classifier in C++. Moreover, we have also implemented all the steps using python for comparative analysis. One of the ...

A full-code demo from Dr. James McCaffrey of Microsoft Research shows how to predict the type of a college course by analyzing grade counts for each type of course. General naive Bayes classification ...

See what features you can expect from Azure Machine Learning and IBM Watson to decide which artificial intelligence solution is right for you. With the ability to revolutionize everything from ...

Notice that all the data values are categorical (non-numeric). This is a key characteristic of the naive Bayes classification technique presented in this article . If you have numeric data, such as a ...

Abstract: Webshell is a command-page document that exists in the form of execution of the program, also known as a backdoor, is an essential means of hacking website uses. Due to the great harm of ...