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 ...
This work leveraged predictive modeling techniques in machine learning (ML) to predict heart disease using a dataset sourced from the Center for Disease Control and Prevention in the US. The dataset ...
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 ...
Abstract: Software developers strive to build high-performance and quality software with a very high degree of coherence among its components, simplified structure, and reduced complexity. A ...
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 ...
A large and growing share of the American public turns to Facebook for news. On this platform, reports about crime increasingly come directly from law enforcement agencies, raising questions about ...
Potentially inappropriate prescribing (PIP), including potentially inappropriate medications (PIMs) and potential prescribing omissions (PPOs), is a major risk factor for adverse drug reactions (ADRs) ...
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