Supervised Ordinal Prediction Task
(Redirected from ordinal regression)
A Supervised Ordinal Prediction Task is a supervised prediction task that is a data-driven ordinal prediction task.
- AKA: Ordinal Regression.
- Context:
- It can be solved by a Supervised Ordinal Prediction System (that implements a supervised ordinal prediction algorithm).
- Example(s):
- Counter-Example(s):
- See: Ordinal Value Prediction.
References
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/ordinal_regression Retrieved:2020-3-30.
- In statistics, ordinal regression (also called "ordinal classification") is a type of regression analysis used for predicting an ordinal variable, i.e. a variable whose value exists on an arbitrary scale where only the relative ordering between different values is significant. It can be considered an intermediate problem between regression and classification. Examples of ordinal regression are ordered logit and ordered probit. Ordinal regression turns up often in the social sciences, for example in the modeling of human levels of preference (on a scale from, say, 1–5 for "very poor" through "excellent"), as well as in information retrieval. In machine learning, ordinal regression may also be called ranking learning.