• Nikita Sawhney
• Dr. Bikrampal Kaur

The credit card fraud detection systems are in the development all across the globe to centralize the health records of all citizens in order to facilitate the flexible provision to all health facilities to the historical health records whenever required. These systems are known to integrate the data of all of the possible diseases together on one platform. These systems can be also used to predict the chances of appearance of disease on the basis of the healthcare analysis done periodically specifically in the developed nations. In this thesis, the work has been performed on the credit card fraud detection. The credit card fraud detection methods are known to claim a number of lives every year across the globe. Hence it becomes important to implement such system, which can predict the chances of committing the fraud in person specific. KNN has been recorded with higher accuracy (approx. 99.95%) than SVM (99.94%) and Logistic Regression (99.92%).

KNN classification, SVM classification, loan fraud, predictive analysis.

"Principal Component Analysis (PCA) based Hyperplane Reallocation with KNN Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.423-425, August-2018, Available :http://www.jetir.org/papers/JETIR1808538.pdf

"Principal Component Analysis (PCA) based Hyperplane Reallocation with KNN Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp423-425, August-2018, Available at : http://www.jetir.org/papers/JETIR1808538.pdf