Supervised Rank Prediction System
(Redirected from Learning-to-Rank System)
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A Supervised Rank Prediction System is a ranking system that is a supervised system and implements a supervised ranking algorithm to solve a supervised ranking task.
- AKA: Ranking Software, Learing-to-Rank System, LTR System.
- Context:
- It can (often) be evaluated using a Supervised Rank Prediction System Evaluation Task.
- It can (often) be developed using a Supervised Ranking Software Framework (such as a ranking software package) or a Supervised Ranking Software Platform (such as ...).
- It can range from being a Supervised Instance-based Ranking System to being a Supervised Model-based Ranking System.
- Example(s):
- Counter-Example(s):
- a Supervised Class Prediction System, that solves a supervised class prediction task.
- a Supervised Rank Prediction System, that solves a supervised rank prediction task.
- a Supervised Numeric Prediction System, that solves a supervised numeric prediction task.
- a Clustering System, that solves an unsupervised clustering task.
- See: Least Squares.