- Data Mining in Finance
- Scientific Discovery and
- Theory and methods
- Comparisons with
- Prediction problem
- Mearsurement theory
- Probabilistic formal
- Induction problem
- Natural classification
- Functional systems
- Computer models
- Financial forecasting
- Forensic Accounting
- Evgenii Vityaev
- Boris Kovalerchuk
Last updated 01/02/2018
Relational Data Mining approach
Our Relational Data Mining approach has the following main points:
1. Any Data Mining method assumes explicitly or implicitly defined:
2. Different DM methods are considered from the point of view of their Data Types, Languages and Hypotheses.
3. Scientific Discovery Theory and the Data Mining Tool Discovery are the ways for further development of various DM methods and include:
We denote the possibility of overcoming limitations of some Data Mining methods concerning particular data types, language to manipulate (interpret) data and hypothesis class to be tested.
The Discovery DM Tool may be considered as a Tool, generating a set of forecasting law-like rules by the specification of Data Types, Invented predicates and Rule Types.
The study of Machine Methods for Discovering Regularities (MMDR) was initiated in the seventies at the Institute of Mathematics, Russian Academy of Sciences.