AIMC Topic: Models, Economic

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Research on the financial early warning models based on ensemble learning algorithms: Introducing MD&A and stock forum comments textual indicators.

PloS one
This study analyzes 284 publicly listed companies first designated as ST or *ST between 2015 and 2023. It utilizes two types of textual indicators: Management's Discussion and Analysis (MD&A) and stock forum comments. PCA and MLP are employed for dim...

A Novel approach to ship valuation prediction: An application to the supramax and ultramax secondhand markets.

PloS one
Accurate ship valuations are very important in ship sales and purchase (S&P) transactions and for marine insurance purposes. It is equally important to select an appropriate valuation methodology. Today, one of the methods is Machine Learning (ML) al...

Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea.

PloS one
The Consumer Price Index (CPI) is a key economic indicator used by policymakers worldwide to monitor inflation and guide monetary policy decisions. In Korea, the CPI significantly impacts decisions on interest rates, fiscal policy frameworks, and the...

A two-stage forecasting model using random forest subset-based feature selection and BiGRU with attention mechanism: Application to stock indices.

PloS one
The heteroscedastic and volatile characteristics of stock price data have attracted the interest of researchers from various disciplines, particularly in the realm of price forecasting. The stock market's non-stationary and volatile nature, driven by...

Innovative entrepreneurial market trend prediction model based on deep learning: Case study and performance evaluation.

Science progress
In the current economic landscape, the growing importance of innovation and entrepreneurship underscores an urgent need for accurate market trend prediction. Addressing this challenge, our study introduces an innovative entrepreneurial market trend p...

Cost-aware active learning for named entity recognition in clinical text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Active Learning (AL) attempts to reduce annotation cost (ie, time) by selecting the most informative examples for annotation. Most approaches tacitly (and unrealistically) assume that the cost for annotating each sample is identical. This ...

Machine Learning for Health Services Researchers.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
BACKGROUND: Machine learning is increasingly used to predict healthcare outcomes, including cost, utilization, and quality.