A brief review of nearest neighbor algorithm for learning and classification

K Taunk, S De, S Verma… - … conference on intelligent …, 2019 - ieeexplore.ieee.org
k-Nearest Neighbor (kNN) algorithm is an effortless but productive machine learning
algorithm. It is effective for classification as well as regression. However, it is more widely …

Machine learning approaches in stock market prediction: A systematic literature review

LN Mintarya, JNM Halim, C Angie, S Achmad… - Procedia Computer …, 2023 - Elsevier
Predicting the stock market has been done for a long time using traditional methods by
analyzing fundamental and technical aspects. With machine learning, stock market …

Predicting short-term stock prices using ensemble methods and online data sources

B Weng, L Lu, X Wang, FM Megahed… - Expert Systems with …, 2018 - Elsevier
With the ubiquity of the Internet, platforms such as: Google, Wikipedia and the like can
provide insights pertaining to firms' financial performance as well as capture the collective …

Deep learning-based metaheuristic weighted k-nearest neighbor algorithm for the severity classification of breast cancer

SRS Chakravarthy, N Bharanidharan, H Rajaguru - IRBM, 2023 - Elsevier
Objective The most widespread and intrusive cancer type among women is breast cancer.
Globally, this type of cancer causes more mortality among women, next to lung cancer. This …

An integrated approach of ensemble learning methods for stock index prediction using investor sentiments

S Deng, Y Zhu, Y Yu, X Huang - Expert Systems with Applications, 2024 - Elsevier
It has been evidenced by numerous studies that irrational investor sentiment is one of the
critical factors leading to dramatic volatility in financial market prices. Therefore, how to …

Advanced stock price prediction with xlstm-based models: Improving long-term forecasting

X Fan, C Tao, J Zhao - 2024 11th International Conference on …, 2024 - ieeexplore.ieee.org
Stock price prediction has long been a critical area of research in financial modeling. The
inherent complexity of financial markets, characterized by both short-term fluctuations and …

[PDF][PDF] A review on analysis of k-nearest neighbor classification machine learning algorithms based on supervised learning

M Suyal, P Goyal - International Journal of Engineering Trends …, 2022 - researchgate.net
Machine learning is a small part of artificial intelligence. Machine learning is one of the most
trending technologies in the world today. Whatever you search on Google, Google takes …

Fake news detection using machine learning and deep learning algorithms

A Abdulrahman, M Baykara - 2020 international conference on …, 2020 - ieeexplore.ieee.org
Classification of fake news on social media has gained a lot of attention in the last decade
due to the ease of adding fake content through social media sites. In addition, people prefer …

[HTML][HTML] Dynamic portfolio optimization with inverse covariance clustering

Y Wang, T Aste - Expert Systems with Applications, 2023 - Elsevier
Market conditions change continuously. However, in portfolio investment strategies, it is hard
to account for this intrinsic non-stationarity. In this paper, we propose to address this issue by …