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@article{156004,
        author = {Prakher Nigam and Chirayu Negi and Rishabh Jain and Himanshu Pandey},
        title = {Design of machine learning classifier for stock market prediction},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {2},
        pages = {668-675},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156004},
        abstract = {The stock market is extremely difficult to predict due to its complexity. There are various machine learning techniques are available to predict the diseases [7,11], stock market and so on. There are on predicting the stock market values. In current scenario in stock market forecasting are done using the Machine Learning and artificial Intelligence which makes the prediction process easier and based on the values of current stock rate by training on the previous values. There are different kind of model that can helps in predicting the stock market. We studied about many models like LSTM, ARIMA model etc. and at the end we seen that For short time series, ARIMA is one of the best models for predicting stock market prices. },
        keywords = {ARIMA model, LSTM, ACF, PACF, AIC},
        month = {},
        }