Mechanizing Hypothesis Formation: Principles and Case Studies

ISBN-13: 9780367549800 / Angielski / Twarda / 2022 / 346 str.

Petr Masa

Opis

The GUHA is a method of mechanizing hypothesis formation. The input of the GUHA procedure consists of analysed data and several parameters defining a large set of relevant patterns. The output is a representation of a set of all relevant patterns satisfying the given true condition.

Spis treści

1. Introduction  2. Data Sets  SECTION I: THE GUHA PROCEDURES  3. Principle and Simple Examples  4. Common Features  5. LISp-Miner System  SECTION II: APPLYING THE GUHA PROCEDURES  6. Examples Overview  7. 4ft-Miner – GUHA Association Rules  8. CF-Miner – Histograms  9. KL-Miner – Pairs of Categorical Attributes  10. SD-4ft-Miner – Couples of GUHA Association Rules  11. SDCF-Miner – Couples of Histograms  12. SDKL-Miner – Couples of Pairs of Categorical Attributes  13. Ac4ft-Miner – Action Rules  14. GUHA Procedures and Business Intelligence  15. CleverMiner – GUHA and Python  SECTION III: RELATED RESEARCH AND THEORY  16. Artificial Data Generation and LM ReverseMiner Module  17. Applying Domain Knowledge  18. Observational Calculi