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The ability to verify the critical risk factors related to an effective diagnosis is very crucial for improving accuracy on coronary heart disease prediction. The objective of this research is to find the best predictive model for coronary heart disease diagnosis. Three approaches are set up to achieve the goals (1) investigating the classifier algorithms…

The effects of Covid-19 severely affected the Thai higher education model. Therefore, there are three significant objectives in this research: (1) to cluster the mindsets and attitudes toward self-regulated learning styles of undergraduate students at the University of Phayao. (2) to construct a predictive model for recommending an appropriate student learning clusters. (3) to evaluate…

In the last few years of research and innovations, lots of spatial data in the form of points, lines, polygons and circles have been made available. Traditional indexing methods are not perfect to store spatial data. To search for nearest neighbour is one of the challenges in different fields like spatiotemporal data mining, computer vision,…

The main assets of universities are students. The performance of students plays a vital role in producing excellent graduate students who will be the future viable leader and manpower in charge of a country’s financial and societal progress. The purpose of this research is to develop a “University Students Result Analysis and Prediction System” that…

Predicting trainees’ final academic results in the early stage of programming class is a significant mission in the field of learning analytics. Performing exercises in programming class is hard and it takes a lot of time for trainees. For this reason, careful support with trainees are offered in many classes through classroom assistants (CAs). Even…

Clustering is a branch of data mining which involves grouping similar data in a collection known as cluster. Clustering can be used in many fields, one of the important applications is the intelligent text clustering. Text clustering in traditional algorithms was collecting documents based on keyword matching, this means that the documents were clustered without…

Currently, one of the challenges of educational institutions is drop-out student issues. Several factors have been found and determined potentially capable to stimulate dropouts. Many researchers have been applied data mining methods to analyze, predict dropout students and also optimize finding dropout variables in advance. The main objective of this study is to find the…

From the collection of supervised machine learning technique, an ensemble procedure is used in Random Forest. In the arena of Data mining, there is an excellent claim for machine learning techniques. Random Forest has tremendous latent of becoming a widespread technique for forthcoming classifiers as its performance has been found analogous with ensemble techniques bagging…

With the unprecedented wave of Big Data, the importance of information visualization is catching greater momentum. Understanding the underlying relationships between constituent objects is becoming a common task in every branch of science, and visualization of such relationships is a critical part of data analysis. While the techniques for the visualization of binary relationships are…

This paper is an extended version of the paper originally presented at the International Conference on Machine Learning and Applications (ICMLA 2016), which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3 segments of a Bank’s…

A company’s ability to find the most profitable technology is based on a precise forecast of achievement potential. Technology Management (TM) uses forecasting models to analyse future potentials, e.g. the Gartner Hype Cycle, Arthur D. Little’s technology lifecycle or McKinsey’s S-curve model. All these methods are useful for qualitative analysis in the planning of strategic…

Discretization is the process of converting numerical values into categorical values. Contemporary literature study reveals that there are many techniques available for numerical data discretization. The performance of classification method is dependent on the exploitation of the data discretizing method. In this article, we investigate the effect of discretization methods on the performance of associative…

Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various…

Among the most popular methodologies for development of data mining projects are CRISP-DM and SEMMA, This research paper explains the reason why it was decided to compare them from a specific case study. Therefore, this document describes in detail each phase, task and activity proposed by each methodology, applying it in the construction of a…

Precision agriculture in recent times had assumed a different dimension in order to improve on the poor standard of agriculture. Similarly, the upsurge in technological advancement, most especially in the aspect of machine learning and artificial intelligence, is a promising trend towards a positive solution to this problem. Therefore, this research work presents a decision…

Senior projects allow students to move the learning process from basic knowledge to an interdisciplinary approach. The purpose of this research is (1) to analysis attitude and perception, which is a collaboration between teachers and students to develop a model for clustering of appropriate advisors and advisee who cooperate in senior project, and (2) to…