customers (Ling and Yen, 2001). The automated data mining tools made it possible to move beyond the analyses of the past events and data mining tools can be used to address problems that were seen as too time-consuming in the past, providing new opportunities for businesses within relationship management. This report identified that CHAID and neural networks are two of the most commonly used data mining techniques within CRM domain. However, each of these techniques has advantages and drawbacks, which should…

A Study of Data Mining Tools and Techniques in Criminology Abstract: Data mining is the process of extracting knowledge from large data sets. It uses artificial intelligence methods to discover the hidden relationships among the huge amount of data that is collected. It has a great potential to improve applications in many fields like Healthcare systems, Customer relationship management, Financial banking, Research analysis, Bio informatics, Marketing analysis, Education, Manufacturing engineering…

Abstract: The Clustering is a data mining technique used to place data elements into related groups without advance knowledge of the group description, which is a division of data into groups of similar objects. The data representing by fewer clusters necessarily loses certain fine details, but achieves generalization. It models data by its clusters. The data modeling puts clustering in a historical perspective rooted in statistics, numerical analysis and mathematics. In this paper represents the…

Data Mining Techniques and Their Applications Deepika Sattu, 800721246, dsattu@uncc.edu Abstract— Data mining is logical process that is used to extract or “mining” large amount of data in order to find useful data [2]. Knowledge discovery from Data or KDD is synonym for Data Mining[13].There are many different types of techniques that can be used to retrieve information from large amount of data. Each type of technique will generate different results. The type of data mining technique…

Abstract Data mining is the process of extracting hidden information from the large data set. Data mining techniques makes easier to predict hidden patterns from the data. The most popular data mining techniques are classification, clustering, regression, association rules, time series analysis and summarization. Classification is a data mining task, examines the features of a newly presented object and assigning it to one of a predefined set of classes. In this research work data mining classification…

Data Mining Techniques and Their Applications in Financial Data Analysis Deepika Sattu, 800721246, dsattu@uncc.edu Abstract— Data mining is a logical process that is used to search through large amount of data in order to find useful data [2].There are many different types of analysis that can be done in order to retrieve information from big data. Each type of analysis will have a different impact or result. Which type of data mining technique you should use really depends on the type…

Literature Review and Data Analysis Teacher-Student Interactions The essence of this project is grounded in the understanding of the student-teacher relationship. In examining current literature that relates to this focus, there are evident themes that arise from the research. This research project will attempt to interpret the influence gender has on the student-teacher relationship by analyzing teacher-student interactions, classroom participation, and discipline. Some researchers suggest…

Data Mining is a technique used in various domains to give meaning to the available data and different types of Data to be handled like numerical data, non-numeric data, image data...etc. In classification tree modelling the data is classified to make predictions about new data. Using old data to predict new data has the danger of being too fitted on the old data. In this we evaluated different types of data to be collected from UCI repository for classify the data using the different classification…

few decades has been the ability to bring tremendous complex and large data sets into database management that are both affordable and workable for many organizations. Improvement in computer power has also allowed for the field of artificial intelligence to evolve which also improves the sifting of massive amounts of information for appropriate use in business, military, governmental, and academic venues. Essentially, data mining is taking as much information as possible for a variety of databases…

Techniques for privacy preserving data mining Introduction Data mining techniques provide good results only if input data is accurate. But data collected from users are often inaccurate.Users may deliberately enter inaccurate information if they are asked to provide personal information because of their worry that information may be misused by organisation to harass them. So we need to find data mining techniques that encourages the user to provide accurate information by ensuring them that…