Rank regression

The rank regression is a simple technique which engages replacing the data with their corresponding ranks. Additionally, we simply fit a line through the (rank of the) points and therefore no assumptions are needed to employ this approach.

1. Is ranking a regression problem?
2. What is ordinal regression used for?
3. How does quantile regression work?

Is ranking a regression problem?

Learning to Rank becomes a regression problem when you build a model to predict the grade as a function of ranking-time signals. Recall from Relevant Search we term signals to mean any measurement about the relationship between the query and a document.

What is ordinal regression used for?

Ordinal regression is a statistical technique that is used to predict behavior of ordinal level dependent variables with a set of independent variables. The dependent variable is the order response category variable and the independent variable may be categorical or continuous.

How does quantile regression work?

Quantile regression determines the median of a set of data across a distribution based on the variables within that distribution. It is an extension of the linear method of regression. This explains why the averages of quantile analysis are not constant as against the linear regression method.