| Extracting The Best Features For Predicting The Trend Of Tehran Stock Exchange (TSE) |
| کد مقاله : 1100-CFIS (R1) |
| نویسندگان |
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فرزانه اکبرزاده *1، علی سلیمانی ایوری2 1دانشکده مهندسی کامپیوتر، دانشگاه صنعتی شاهرود، شاهرود، ایران 2دانشکده مهندسی کامپیوتر، دانشگاه صنعتی شاهرود، شاهرود، ایران |
| چکیده مقاله |
| Predicting stock price trend is an important task as well as difficult problem. This prediction depends on various factors and their complex relationships. Feature extraction is a way to discover these factors from initial data. In this paper, several famous feature extraction methods are proposed as a data engineering approach for TSE. The results of predicting next day trend by k-Nearest Neighbors (kNN) predictor, shows indicators are best extracted features. |
| کلیدواژه ها |
| stock, trend prediction, feature extraction method, kNN |
| وضعیت: پذیرفته شده برای ارائه شفاهی |