Feature Sequential Selection Process for Predicting Disease Glomerulonephritis

Kidneys are important to have beneficial body.They are basically answerable for separating side-effects,abundance water and various debasements out of the blood.Toxins are saved within inside the bladder after which eliminated all through urination. Glomerulonephritis is one of the difficult nephrotic disorder that happens with inside the transplanted kidneys. The severity of the disorder may be anticipated with the aid of using the usage of the clinical data. Classification results had been procured the usage of 3 exclusive overall performance criteria using three different performance criteria(Kappa, Area beneath the ROC curve).Data Mining will yield great outcomes when applied with the tools and procedures.Diagnosing methods can be improved by selecting various attributes and features. Redundancy of data continuously increases day to day. To avoid such redundancy sequential selection method is used. Feature selection method focuses on input space but whereas the sequential method focuses on reduced data consumption. To reduce the data dimensionality feature selection procedure is used.To reduce data dimensionality and provide a high accuracy the proposed method is used.