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- Nadkarni P M, Ohno-Machado L, Chapman W W. Natural language processing: an introduction[J]. Journal of the American Medical Informatics Association, 2011, 18(5): 544-551.Google ScholarCross Ref
- Devlin J, Chang M W, Lee K, Bert: Pre-training of deep bidirectional transformers for language understanding[J]. arXiv preprint arXiv:1810.04805, 2018.Google Scholar
- Sarzynska-Wawer J, Wawer A, Pawlak A, Detecting formal thought disorder by deep contextualized word representations[J]. Psychiatry Research, 2021, 304: 114135.Google ScholarCross Ref
- Wolf T, Chaumond J, Debut L, Transformers: State-of-the-art natural language processing[C]//Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. 2020: 38-45.Google Scholar
- Rong X. word2vec parameter learning explained[J]. arXiv preprint arXiv:1411.2738, 2014.Google Scholar
- Chen T, Guestrin C. Xgboost: A scalable tree boosting system[C]//Proceedings of the 22nd Acm Sigkdd International Conference on Knowledge Discovery and Data Mining. 2016: 785-794.Google Scholar
- Svetnik V, Liaw A, Tong C, Random forest: a classification and regression tool for compound classification and QSAR modeling[J]. Journal of Chemical Information and Computer Sciences, 2003, 43(6): 1947-1958.Google ScholarCross Ref
- Tucker J, Tucker D J. Neural networks versus logistic regression in financial modelling: A methodological comparison[C]//Proceedings of the 1996 World First Online Workshop on Soft Computing (WSC1). 1996.Google Scholar
- Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation[C]//International Conference on Medical Image Computing and Computer-assisted Intervention. Springer, Cham, 2015: 234-241.Google Scholar
- Zhou Y, Ren F, Nishide S, Facial sentiment classification based on resnet-18 model[C]//IEEE International Conference on Electronic Engineering and Informatics (EEI). 2019: 463-466.Google Scholar
- Gajarla V, Gupta A. Emotion detection and sentiment analysis of images[J]. Georgia Institute of Technology, 2015: 1-4.Google Scholar
- De Chaisemartin C, d'Haultfoeuille X. Two-way fixed effects estimators with heterogeneous treatment effects[J]. American Economic Review, 2020, 110(9): 2964-96.Google ScholarCross Ref
- Halder S C, Malikov E. Smoothed LSDV estimation of functional-coefficient panel data models with two-way fixed effects[J]. Economics Letters, 2020, 192: 109239.Google ScholarCross Ref
- Shen H, Zheng S, Xiong H, Stock market mispricing and firm innovation based on path analysis[J]. Economic Modelling, 2021, 95: 330-343.Google ScholarCross Ref
- Zhao F, Gao Y, Li X, A similarity measurement for time series and its application to the stock market[J]. Expert Systems with Applications, 2021, 182: 115217.Google ScholarDigital Library
- Wu D, Wang X, Su J, A labeling method for financial time series prediction based on trends[J]. Entropy, 2020, 22(10): 1162.Google ScholarCross Ref
- Zhong Z, Yuan X, Liu S, Machine learning prediction models for prognosis of critically ill patients after open-heart surgery[J]. Scientific Reports, 2021, 11(1): 1-10.Google ScholarCross Ref
- Ayala J, García-Torres M, Noguera J L V, Technical analysis strategy optimization using a machine learning approach in stock market indices[J]. Knowledge-Based Systems, 2021, 225: 107119.Google ScholarCross Ref
- Kumar D, Sarangi P K, Verma R. A systematic review of stock market prediction using machine learning and statistical techniques[J]. Materials Today: Proceedings, 2021.Google Scholar
- Prachyachuwong K, Vateekul P. Stock Trend Prediction Using Deep Learning Approach on Technical Indicator and Industrial Specific Information[J]. Information, 2021, 12(6): 250.Google ScholarCross Ref
- Jing N, Wu Z, Wang H. A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction[J]. Expert Systems with Applications, 2021, 178: 115019.Google ScholarCross Ref
- Bao Z, Wei Q, Zhou T, Predicting stock high price using forecast error with recurrent neural network[J]. Applied Mathematics and Nonlinear Sciences, 2021, 6(1): 283-292.Google ScholarCross Ref
- Dong W, Zhao C. Stock price forecasting based on Hausdorff fractional grey model with convolution and neural network[J]. Mathematical Biosciences and Engineering, 2021, 18(4): 3323-3347.Google ScholarCross Ref
- Vo-Van T, Che-Ngoc H, Le-Dai N, A New Strategy for Short-Term Stock Investment Using Bayesian Approach[J]. Computational Economics, 2021: 1-25.Google Scholar
- Soujanya R, Goud P A, Bhandwalkar A, Evaluating future stock value asset using machine learning[J]. Materials Today: Proceedings, 2020, 33: 4808-4813.Google ScholarCross Ref
- Mehta P, Pandya S, Kotecha K. Harvesting social media sentiment analysis to enhance stock market prediction using deep learning[J]. PeerJ Computer Science, 2021, 7: e476.Google ScholarCross Ref
- McKinney W. pandas: a foundational Python library for data analysis and statistics[J]. Python for High Performance and Scientific Computing, 2011, 14(9): 1-9.Google Scholar
- Kramer O. K-nearest neighbors [M]//Dimensionality Reduction with Unsupervised Nearest Neighbors. Springer, Berlin, Heidelberg, 2013: 13-23.Google ScholarDigital Library
- Myles A J, Feudale R N, Liu Y, An introduction to decision tree modeling[J]. Journal of Chemometrics: A Journal of the Chemometrics Society, 2004, 18(6): 275-285.Google ScholarCross Ref
- Webb G I, Keogh E, Miikkulainen R. Naïve Bayes[J]. Encyclopedia of Machine Learning, 2010, 15: 713-714.Google Scholar
- Noble W S. What is a support vector machine?[J]. Nature Biotechnology, 2006, 24(12): 1565-1567.Google ScholarCross Ref
- Whitley D. Genetic algorithms and neural networks[J]. Genetic Algorithms in Engineering and Computer Science, 1995, 3: 191-201.Google Scholar
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