เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| ความน่าจะเป็นที่ไม่แม่นยำ× | ทฤษฎีความเป็นไปได้× | |
|---|---|---|
| สาขาวิชา | การคำนวณแบบอ่อน | การคำนวณแบบอ่อน |
| ตระกูล≠ | Bayesian methods | Machine learning |
| ปีกำเนิด≠ | 1991 | 1988 |
| ผู้ริเริ่ม≠ | Peter Walley | Lotfi Zadeh; Didier Dubois & Henri Prade |
| ประเภท≠ | Set-valued probability model | Uncertainty quantification framework |
| แหล่งต้นตำรับ≠ | Walley, P. (1991). Statistical Reasoning with Imprecise Probabilities. Chapman & Hall. ISBN: 978-0-412-28660-5 | Dubois, D., & Prade, H. (1988). Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press. ISBN: 978-0-306-42520-2 |
| ชื่อเรียกอื่น | Lower-Upper Probability, Robust Bayesian Analysis, Credal Set Theory, Belirsiz Olasılık | Fuzzy Possibility Theory, Possibilistic Reasoning, Olasılık Teorisi (Bulanık), Possibility Distribution Theory |
| ที่เกี่ยวข้อง | 3 | 3 |
| สรุป≠ | Imprecise probability is a generalization of standard probability theory that represents epistemic uncertainty through sets of probability measures, called credal sets, rather than a single precise distribution. Introduced systematically by Peter Walley in his 1991 monograph, the framework characterizes beliefs via lower and upper probabilities (or previsions), bracketing the range of plausible probability assignments when available information is insufficient to determine a unique measure. | Possibility Theory is a mathematical framework for representing and reasoning under uncertainty, introduced by Lotfi Zadeh in 1978 and systematically developed by Didier Dubois and Henri Prade in their 1988 monograph. It uses possibility distributions — functions assigning a degree in [0,1] to each element of a universe — to encode what is plausible or consistent with available information, complementing probability theory for situations where data is scarce or knowledge is imprecise. |
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