Abstract:
In this paper, we used two models of outlier detection techniques in which the first model talks about
Application of Data Mining Techniques for Outlier Mining in Medical Databases and the second model
throws light on Outlier Mining in Medical Databases by UsingStatistical Methods. Both the
models emphasizes on detecting the outliers in the medical databases by the way of mining
through the entire database. First model makes use of the statistical analysis tools for the work
and takes care of complicated issues in terms of patient symptoms, diagnoses and behaviors and
hence they are said to be the most promising arenas of outlier determination. In second model
outliers of 5 datasets; them being leverage, R-standard, R-student, DFFITS, Cook’s D and
covariance ratio are taken care off and explained.
