This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple data set, then proceeds to explain how one might approach a bioinformatics problem. Finally, it includes a brief summary of machine learning algorith...

-Data Mining is a powerful tool for academic intervention. Mining in education environment is called Educational Data Mining. Educational Data Mining is concerned with developing new methods to discover knowledge from educational database and can used for decision making in educational system. In our work, we collected the student’s data from engineering institute that have different informatio...

—The SOA philosophy can address new business challenges, become more competitive and provide integrated information systems. In addition, technologies such as BPM, BAM and Web Services are essential complements to SOA. This work aims to use several of these technologies integrated into a single application that will allow in a phase of a previously defined business process, to perform the analy...

A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. WEKA is a collection of machine learning algorithms for solving real-world data mining problems. It is writ...

Cardiovascular diseases remain the most prevalent cause of deaths worldwide and their prevention requires major life-style changes using limited health-care resources. Remote decision support for cardiovascular patients seems to allow them to lead a productive life and to minimize the costs of treatment. In this paper, risk estimation of cardiovascular patients on the basis of collected data us...

We exhibited the thought of data mining through the free and open source programming Waikato Environment for Knowledge Analysis (WEKA), which allows you to burrow own data for examples and cases. We moreover depicted about the first methodology for data mining — backslide — which allows you to anticipate a numerical worth for a given set of insight qualities. This method for dismemberment is mo...

—Data mining is also being useful to give solutions for invasion finding and auditing. While data mining has several applications in protection, there are also serious privacy fears. Because of email mining, even inexperienced users can connect data and make responsive associations. Therefore we must to implement the privacy of persons while working on practical data mining. Using K-mean cluste...

-We are live in a time there we used a huge amount and useful information and we want to save the time for this reason we use the data mining. Today we are using the electronic devices to store the information they have ability to save the very large amount of information so that to operate the information manually is very difficult and time consuming thus we use the data mining. Data mining de...

Intrusion detection is one of the major research problems in network security. It is the process of monitoring and analyzing the events occurring in a computer system in order to detect different security violations. The aim of this paper is to classify activities of a system into two major categories: normal and abnormal activities. In this paper we present the comparison of different classifi...