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Survey of feature selection and extraction techniques for stock market prediction
In stock market forecasting, the identification of critical features that affect the performance of
machine learning (ML) models is crucial to achieve accurate stock price predictions. Several …
machine learning (ML) models is crucial to achieve accurate stock price predictions. Several …
Explainable artificial intelligence in finance: A bibliometric review
XQ Chen, CQ Ma, YS Ren, YT Lei, NQA Huynh… - Finance Research …, 2023 - Elsevier
This study focuses on explainable artificial intelligence (XAI) in finance. We collected 2,733
articles published between 2013 and 2023 from the Web of Science Core Collection and …
articles published between 2013 and 2023 from the Web of Science Core Collection and …
[HTML][HTML] An overview of variational autoencoders for source separation, finance, and bio-signal applications
Autoencoders are a self-supervised learning system where, during training, the output is an
approximation of the input. Typically, autoencoders have three parts: Encoder (which …
approximation of the input. Typically, autoencoders have three parts: Encoder (which …
Integrated multiple directed attention-based deep learning for improved air pollution forecasting
In recent years, human health across the world is becoming concerned by a constant threat
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …
Optimizing investment portfolios with a sequential ensemble of decision tree-based models and the FBI algorithm for efficient financial analysis
JS Chou, KE Chen - Applied Soft Computing, 2024 - Elsevier
This research presents a comprehensive, sequential ensemble framework meticulously
crafted for optimizing investment portfolios, focusing on the construction industry. It employs …
crafted for optimizing investment portfolios, focusing on the construction industry. It employs …
Extending machine learning prediction capabilities by explainable AI in financial time series prediction
Prediction with higher accuracy is vital for stock market prediction. Recently, considerable
amount of effort has been poured into employing machine learning (ML) techniques for …
amount of effort has been poured into employing machine learning (ML) techniques for …
Simulated annealing aided genetic algorithm for gene selection from microarray data
S Marjit, T Bhattacharyya, B Chatterjee… - Computers in Biology and …, 2023 - Elsevier
In recent times, microarray gene expression datasets have gained significant popularity due
to their usefulness to identify different types of cancer directly through bio-markers. These …
to their usefulness to identify different types of cancer directly through bio-markers. These …
A stock market trading framework based on deep learning architectures
Market prediction has been a key interest for professionals around the world. Numerous
modern technologies have been applied in addition to statistical models over the years …
modern technologies have been applied in addition to statistical models over the years …
[HTML][HTML] A hybrid framework based on extreme learning machine, discrete wavelet transform, and autoencoder with feature penalty for stock prediction
Accurate prediction of the stock market trend can assist efficient portfolio and risk
management. In recent years, with the rapid development of deep learning, it can make the …
management. In recent years, with the rapid development of deep learning, it can make the …
A forecasting framework for the Indian healthcare sector index
J Sen - International Journal of Business Forecasting and …, 2022 - inderscienceonline.com
Forecasting of future stock prices is a complex and challenging research problem due to the
random variations that the time series of these variables exhibit. In this work, we study the …
random variations that the time series of these variables exhibit. In this work, we study the …