• Nikita Mandrah
• Dr. Ashish Kumar Khare

News is crucial part of our life. In day to day life current news are helpful to enhance knowledge what happen around the world. So most of peoples prefer watching news most of the peoples generally prefer reading newspaper early in the morning enjoying with cup of tea. If news is fake that will mislead peoples sometimes fake news utilized to spread rumors about things or it will affect some political leader positions just because of fake news. So it’s crucial to find the fake news. This paper proposed a optimized system to detect fake news, but now a day’s data on web or social media is increasing vastly and it is so hectic to detect news is fake or not by looking all data and it is time consuming so we utilize classification techniques to classify huge data. Here we proposed fake news detection system based on classification such as Naïve bayes (NB), and Support vector machine (SVM), decision tree (DT) and K Nearest Neighbor (KNN). We compare all machine learning techniques for detecting fake news.

Machine Learning, Fake News, KNN, DT, NB, SVM, Python

"An Efficient Approach based on Machine Learning and Performance Improvement for Fake News Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.331-336, April-2021, Available :http://www.jetir.org/papers/JETIR2104045.pdf

"An Efficient Approach based on Machine Learning and Performance Improvement for Fake News Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp331-336, April-2021, Available at : http://www.jetir.org/papers/JETIR2104045.pdf