Difference between revisions of "Ordinal Regression"
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[http://www.youtube.com/results?search_query=Ordinal+Regression YouTube search...] | [http://www.youtube.com/results?search_query=Ordinal+Regression YouTube search...] | ||
| + | [http://www.google.com/search?q=Ordinal+Regression+deep+machine+learning+ML+artificial+intelligence ...Google search] | ||
| − | * [[AI Solver]] | + | * [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Train, Validate, and Test]] |
| − | * [[...predict values]] | + | ** [[...predict values]] |
| − | * [[ | + | * [[Regression]] Analysis |
| − | * [https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/ordinal-regression Ordinal Regression | Microsoft] | + | * [[Math for Intelligence]] ... [[Finding Paul Revere]] ... [[Social Network Analysis (SNA)]] ... [[Dot Product]] ... [[Kernel Trick]] |
| + | * [https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/ordinal-regression Ordinal Regression |] [[Microsoft]] | ||
| + | * [http://statisticsbyjim.com/regression/choosing-regression-analysis/ Choosing the Correct Type of Regression Analysis | Jim Frost] | ||
(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. [http://en.wikipedia.org/wiki/Ordinal_regression Wikipedia] | (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. [http://en.wikipedia.org/wiki/Ordinal_regression Wikipedia] | ||
Latest revision as of 21:49, 5 March 2024
YouTube search... ...Google search
- AI Solver ... Algorithms ... Administration ... Model Search ... Discriminative vs. Generative ... Train, Validate, and Test
- Regression Analysis
- Math for Intelligence ... Finding Paul Revere ... Social Network Analysis (SNA) ... Dot Product ... Kernel Trick
- Ordinal Regression | Microsoft
- Choosing the Correct Type of Regression Analysis | Jim Frost
(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. Wikipedia
Some examples of ranked values:
- Survey responses that capture user’s preferred brands on a 1 to 5 scale
- The order of finishers in a race
- URLs in ranked search results
