Benefits of Machine Learning and Artificial Intelligence -- Machine Learning -- Best Practices -- Setting Up the R Development Environment -- Fundamentals of the R Programming Language -- Machine Learning with R -- Application of Machine Learning with R -- Outlook.

The study's objective is to check whether the predictive power of Machine Learning Techniques is better than Logistic Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a proxy for uncertainty is added to the model as a...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

The paper develops an early warning system to identify banks that could face liquidity crises. To obtain a robust system for measuring banks’ liquidity vulnerabilities, we compare the predictive performance of three models – logistic LASSO, random forest and Extreme Gradient Boosting – and...

This study applies machine learning models to explore the predictive power of ten categories of financial indicators in Chinese stock market. Meanwhile, we assess whether influential financial indicators cluster into specific categories that hold greater importance for stock return prediction....