Cardinality refers to the number of possible values that a feature can assume. For example, the variable “US State” is one that has 50 possible values. The binary features, of course, could only assume one of two values (0 or 1). The values of a categorical variable are selected from Read more…
Missing data, or missing values, occur when no data / no value is stored for certain observations within a variable. Incomplete data is an unavoidable problem in most data sources, and may have a significant impact on the conclusions that can be derived from the data. Why is data missing? The source of missing Read more…
Feature Selection using Fisher Score and Chi2 (χ2) Test Watch Full Playlist: https://www.youtube.com/playlist?list=PLc2rvfiptPSQYzmDIFuq2PqN2n28ZjxDH What is Fisher Score and Chi2 ( χ2) Test Fisher score is one of the most widely used supervised feature selection methods. However, it selects each feature independently according to their scores under the Fisher criterion, which Read more…