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Understanding random operating curves or ROC analysis

By Priya Chetty on September 18, 2018 No Comments

Receiver Operating Curve (ROC) is an extension of such classifications. Performance of binary classifier system in the case of ROC analysis can be tested.

 classification in supervised learning, Supervised learning

How to use K-Nearest Neighbor (KNN) algorithm on a dataset?

By Prateek Sharma and Priya Chetty on July 16, 2018 2 Comments

K- Nearest Neighbor, popular as K-Nearest Neighbor (KNN), is an algorithm that helps to assess the properties of a new variable with the help of the properties of existing variables. KNN is applicable in classification as well as regression predictive problems.

 analyse with SPSS, classification in supervised learning, Supervised learning, trend discovery

Solving complicated problems with decision tree

By Priya Chetty on January 10, 2018 No Comments

A decision tree is a graphical representation of possible solutions to a problem based on given conditions. It is called a tree because diagrammatically it starts with a single box (target variable) and ends up in numerous branches and roots (numerous solutions).

 classification in supervised learning, Supervised learning, trend discovery

How to apply linear discriminant analysis?

By Priya Chetty on December 13, 2017 1 Comment

Linear discriminant model is a multivariate model. It is used for modeling the differences in groups. In this model a categorical variable can be predicted through continuous or binary dependent variable.

 classification in supervised learning, Supervised learning
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