STOCK PRICE PREDICTION USING SUPPORT VECTOR REGRESSION AND K-NEAREST NEIGHBORS: A COMPARISON

Abstract

Supervised Learning is an important type of Machine learning. It includes regression and classification problems. In Supervised learning, Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) can be used for classification and regression. Here, both algorithms are used for regression problem. The stock data is trained by SVR and KNN respectively to predict the stock price of the next day using python tool. Both algorithms are compared and it is observed that the price predicted by SVR is closer as compared to KNN.