Feature Extraction Techniques Using Support Vector Machines in Disease Prediction

  title={Feature Extraction Techniques Using Support Vector Machines in Disease Prediction},
  author={Sandeep Kaur and Dr. Sheetal Kalra},
Data mining process is becoming important in healthcare industry due to very large volume of data produced and collected by them on daily basis. Support Vector Machine is the most commonly used classification algorithm for disease prediction in healthcare industry. It is widely used to predict the disease like diabetes, breast cancer, lung cancer, heart disease etc. It is advantageous to reduce the number of input features to Support Vector Machine in order to get efficient results. To reduce… CONTINUE READING


Publications referenced by this paper.
Showing 1-10 of 15 references

Study of Diabetes Prediction using Feature Selection and Classification

K. K. Gandhi, Prajapati, B N., August
In International Journal of Engineering Research and Technology (Vol. 3, No • 2014
View 2 Excerpts

Data Mining techniques : A survey paper

V. Srivastava
IJRET : International Journal of Research in Engineering and Technology • 2013

Comparison of feature selection methods for multiclass cancer classification based on microarray data

2011 4th International Conference on Biomedical Engineering and Informatics (BMEI) • 2011
View 1 Excerpt

Similar Papers

Loading similar papers…