{"title":"使用机器学习模型预测股票市场","authors":"A. Yasmin, S. Kamalakkannan, P. Kavitha","doi":"10.1109/ICECAA55415.2022.9936188","DOIUrl":null,"url":null,"abstract":"Stock market prediction is the needed emerging economic statistics from business to normal middle-class peoples, to make their investment as a profitable one. This article has utilized the dynamic dataset of the company. The dataset includes the closing price of the stock of the last 290 working days. The dataset is downloaded using the yahoo finance (https://finance.yahoo.com), so the data is pretty accurate. Further, some technical analysis and machine learning techniques are used to predict the future prices and exchange of company’s stock. The machine learning models includes Linear Regression, Decision Tree, Random Forest, SVR, LSTM, Lasso Regression, KNN, Bayesian Ridge, Gradient Boosting, and Ada Boost are used in this article and suitable technique for the dataset is chosen for performing effective prediction of stock market.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stock Market Prediction using Machine Learning Models\",\"authors\":\"A. Yasmin, S. Kamalakkannan, P. Kavitha\",\"doi\":\"10.1109/ICECAA55415.2022.9936188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stock market prediction is the needed emerging economic statistics from business to normal middle-class peoples, to make their investment as a profitable one. This article has utilized the dynamic dataset of the company. The dataset includes the closing price of the stock of the last 290 working days. The dataset is downloaded using the yahoo finance (https://finance.yahoo.com), so the data is pretty accurate. Further, some technical analysis and machine learning techniques are used to predict the future prices and exchange of company’s stock. The machine learning models includes Linear Regression, Decision Tree, Random Forest, SVR, LSTM, Lasso Regression, KNN, Bayesian Ridge, Gradient Boosting, and Ada Boost are used in this article and suitable technique for the dataset is chosen for performing effective prediction of stock market.\",\"PeriodicalId\":273850,\"journal\":{\"name\":\"2022 International Conference on Edge Computing and Applications (ICECAA)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Edge Computing and Applications (ICECAA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECAA55415.2022.9936188\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Edge Computing and Applications (ICECAA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECAA55415.2022.9936188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stock Market Prediction using Machine Learning Models
Stock market prediction is the needed emerging economic statistics from business to normal middle-class peoples, to make their investment as a profitable one. This article has utilized the dynamic dataset of the company. The dataset includes the closing price of the stock of the last 290 working days. The dataset is downloaded using the yahoo finance (https://finance.yahoo.com), so the data is pretty accurate. Further, some technical analysis and machine learning techniques are used to predict the future prices and exchange of company’s stock. The machine learning models includes Linear Regression, Decision Tree, Random Forest, SVR, LSTM, Lasso Regression, KNN, Bayesian Ridge, Gradient Boosting, and Ada Boost are used in this article and suitable technique for the dataset is chosen for performing effective prediction of stock market.