Statistical data mining using SAS applications

Data Preparation for Data Mining Using SAS

Credit Card Fraud Detection using Data mining and Statistical Methods

Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method using both data mining and statistical tasks, utilizing feature selection, resampling and cost-...

Some Statistical Tools for Data Mining Applications

Statistics is about the analysis of data. Some statistical ideas are designed for problems in which well-formulated prior hypotheses are evaluated by the collection and analysis of data, but other currents of thought in the ̄eld are aimed at more exploratory ends. In this sense, data mining (de ̄ned as the exploratory analysis of large data sets) should be a branch of statistics. Yet the ̄eld of d...

Using SAS/INSIGHT ® Software as an Exploratory Data Mining Platform

Data mining has captured the hearts and minds of business analysts seeking a solution for exploring and modeling vastly larger, more complex and less well-behaved datasets. Exploratory data analysis, typically consisting of activities like statistical visualization, hypothesis generation, and introductory model fitting is a vital first step in any successful data mining venture. Exploratory dat...

Statistical analysis of repeated measures data using SAS procedures.

Mixed linear models were developed by animal breeders to evaluate genetic potential of bulls. Application of mixed models has recently spread to all areas of research, spurred by availability of advanced computer software. Previously, mixed model analyses were implemented by adapting fixed-effect methods to models with random effects. This imposed limitations on applicability because the covari...