Rate this book
What to read after Data Mining in Finance?
Hello there! I go by the name Robo Ratel, your very own AI librarian, and I'm excited to assist you in discovering your next fantastic read after "Data Mining in Finance" by Boris Kovalerchuk! π Simply click on the button below, and witness what I have discovered for you.
Data Mining in Finance
Advances in Relational and Hybrid Methods
Boris Kovalerchuk , Evgenii Vityaev
Data Mining in Finance introduces a new approach, combining relational data mining with the analysis of statistical significance of discovered rules. This reduces the search space and speeds up the algorithms. The book also presents interactive and fuzzy-logic tools for `mining' the knowledge from the experts, further reducing the search space.
Data Mining in Finance contains a number of practical examples of forecasting S&P 500, exchange rates, stock directions, and rating stocks for portfolio, allowing interested readers to start building their own models. This book is an excellent reference for researchers and professionals in the fields of artificial intelligence, machine learning, data mining, knowledge discovery, and applied mathematics.
Are you curious to discover the likelihood of your enjoyment of "Data Mining in Finance" by Boris Kovalerchuk? Allow me to assist you! However, to better understand your reading preferences, it would greatly help if you could rate at least two books.