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| Name (abbrev) | Name (full) | Category | Last update |
| UTUBE | | Modelling, Diagnosis, Control | b D, Y |
| Application domain | Further specifications |
| Learning qualitative models from example behaviors | dataset = data + background theory |
| Type | Format | Complexity |
| ILP | Prolog (mFOIL format) | 4 positive and 543 negative examples |
| WWW / FTP | |
| ftp://ftp.mlnet.org/ml-archive/ILP/public/data/utube/
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| Contact person(s) | Related group(s) | Optional contact address |
| - Dzeroski, Saso
| - Jozef Stefan Institute, Department of Intelligent
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| References |
| Lavrac, N., Dzeroski,S. Inductive Logic Programming: Techniques and Applications. Ellis Horwood, Chichester, 1994. Chapter 13.
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| Annotations |
| The dataset is intended to learn a QSIM type qualitative model of two connected containerns - a dynamic system, known also as the U-tube. The target predicate legalstate/4 has as arguments the qualitative values of the four system variables (water levels and their rates of change for each of the two containers). Positive facts corresponding to this predicate describe the states that appear in a qualitative behavior of the U-tube (4 facts). Negative facts (543) characterize those states that are impossible in such a system. Background knowledge defines the qualitative constraints of the QSIM formalism: add/3, multiply/3, deriv/2, m_plus/2, m_minus/2, and minus/2. The achieved results are described in [Lavrac 94].
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