This paper is published in Volume-3, Issue-3, 2017
Area
Artificial Intelligence
Author
Gurvir Kaur, Er. Parvinder Kaur
Org/Univ
Shaheed Udham Singh Engineering College, Tangori, Punjab, India
Keywords
NLP, KNN, SVC, Text Classification
Citations
IEEE
Gurvir Kaur, Er. Parvinder Kaur. Novel Approach of Text Classification by SVM-RBF Kernel and Linear SVC, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Gurvir Kaur, Er. Parvinder Kaur (2017). Novel Approach of Text Classification by SVM-RBF Kernel and Linear SVC. International Journal of Advance Research, Ideas and Innovations in Technology, 3(3) www.IJARIIT.com.
MLA
Gurvir Kaur, Er. Parvinder Kaur. "Novel Approach of Text Classification by SVM-RBF Kernel and Linear SVC." International Journal of Advance Research, Ideas and Innovations in Technology 3.3 (2017). www.IJARIIT.com.
Gurvir Kaur, Er. Parvinder Kaur. Novel Approach of Text Classification by SVM-RBF Kernel and Linear SVC, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Gurvir Kaur, Er. Parvinder Kaur (2017). Novel Approach of Text Classification by SVM-RBF Kernel and Linear SVC. International Journal of Advance Research, Ideas and Innovations in Technology, 3(3) www.IJARIIT.com.
MLA
Gurvir Kaur, Er. Parvinder Kaur. "Novel Approach of Text Classification by SVM-RBF Kernel and Linear SVC." International Journal of Advance Research, Ideas and Innovations in Technology 3.3 (2017). www.IJARIIT.com.
Abstract
In suspicion, characteristic dialect handling is an exceptionally brilliant strategy for the human-PC interface. Regular dialect grateful is once in a while alludes to as an Artificial Intelligence-whole issue since normal dialect distinguishing proof appears to include wide learning about the outside world and the capacity to control it. NLP has vital have regular qualities with the field of computational semantics and is frequently viewed as a sub-field of computerized reasoning. In this paper working two learning approaches knn and support vector machine (SVM) yet SVM gives importance great exactness, accuracy, review than KNN, SVC.