Company's Stock Price Predictor using Machine Learning
1Assistant Professor, Dept. of Computer Science Engineering, Datta Meghe Institute of Engineering Technology Research, Wardha, Maharashtra, India 2,3,4,5,6 Student, Dept. of Computer Science Engineering, Datta Meghe Institute of Engineering Technology Research, Wardha, Maharashtra, India Abstract Due to the unsettled, composite and time to time changing of prices, stock market prediction has attracted a lot of interest from investors and researchers for quite a time. It is very difficult to make dependable predictions. The stock market prices are predicted using the machine learning algorithms like k Nearest Neighbors, in this system. The model that has been highly triumphant for classification and regression is the k Nearest Neighbors model. KNN algorithm is a very popular classification algorithm demonstrating good performance characteristics and also a short period of training time. We must specify such sets of neighborhoods that might approve the close neighbors, as stated by K nearest neighbor's distribution. We use Support vector machine for the purpose of classification and it is a machine learning model. This model is also used for classification for most of the times. Based on historical data, this system provides the information whether the price of stock will go up or down using these techniques. This also provides deep knowledge of the models that are used in this process.