Abstract-Data mining is the analysis of a large dataset to discover patterns and use those patterns to predict the likelihood of the future events. Data mining is becoming a very important field in educational sectors and it holds great potential for the schools and universities. There are many data mining classification techniques with different levels of accuracy. The objective of this paper is to analyze and evaluate the university students' performance by applying different data mining classification techniques by using WEKA tool. The highest accuracy of classifier algorithms depends on the size and nature of the data. Five classifiers are used NaiveBayes, Bayesian Network, ID3, J48 and Neural Network Different performance measures are used to compare the results between these classifiers. The results shows that Bayesian Network classifier has the highest accuracy among the other classifiers.
Data mining is the analysis of large datasets to discover patterns and use those patterns to predict the likelihood of the future events. Data mining is becoming a very important field in healthcare sectors and it holds great potential for the healthcare industry. This paper presents an overview of current research being carried out using data mining techniques in different medical areas such as heart disease, diabetes, breast and lung cancer and skin disease by using different data mining techniques to find the best method of prediction and accuracy.
Social networks are websites that enable people to communicate with others, express their opinions, and share their thoughts, experiences, and interests. It also contributes to job creation and facilitates the marketing of various products and services. A cyber threat is the malicious attempt to access a computer network through a data communications pathway by illegal means; they can be intended or unintended, direct or indirect, and are usually carried out by hackers, virus code writers, industrial spies, organized crime unions, vengeful employees and spiteful intruders. This paper presents the history of online social networking and classifies their types; it also discusses cyber threats on social networking websites and puts forward a policy and action plan to counter threats to social networks in the future.
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