Application Of Machine Learning Algorithms To Determine The Default Habits Of A Bank's Creditors
Computational methods are mathematical models used to study the behavior of complex systems using
computer simulation. Computational models are combining different mathematical and statistical tools
that are used to analyze data-sets. These computational models help to understand the relationship between
desired outcome and different factors affecting the outcome in order to solve problems. Machine
learning is a data analysis method that automates building of analytical models by using algorithms that
learn from data and hidden insights without being programmed where to look. For example, investment
banks use computational models to determine how to buy or sell shares in the stock market in order
to make a prot or liquidate their holdings in order to avoid losses. Due to dynamic nature of the stock
market, investment banks need to make investment decisions quickly, and therefore constantly feed new
and updated data to a computer which then uses machine learning algorithms to generate new models.
This study analyzes the accuracy of three different computational methods that were generated using machine
learning techniques