Data Transformation and Reduction

In this repository , I have used Pima Indians Diabetes Database as a csv file for attribute normalization, standardization and dimension reduction. This data-set is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective is to predict based on diagnostic measurements whether a patient has diabetes. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females with at least 21 years old of Pima Indian heritage.
It contains following 9 attributes :-
1.pregs: Number of times pregnant
2.plas: Plasma glucose concentration 2 hours in an oral glucose tolerance test
3.pres: Diastolic blood pressure (mm Hg)
4.skin: Triceps skin fold thickness (mm)
5.test: 2-Hour serum insulin (mu U/mL)
6.BMI: Body mass index (weight in kg/(height in m)^2)
7.pedi: Diabetes pedigree function
8.Age: Age (years)
9.class: Class variable (0 or 1)