Howtosignalprocessing
- What is an example of feature redundancy?
- What are the redundant features?
- What is a redundant feature in machine learning?
- Do redundant features affect classifier performance?
What is an example of feature redundancy?
A simple example of a redundant feature is one which is never (or always) satisfied: e.g., 'a molecule having an atom which has a bond with itself'. While some forms of redundancy can be recognised at feature generation time, others can only come to light by examining the data.
What are the redundant features?
Redundant features are those that are correlated with other features and not relevant in the sense that they do not improve the discriminatory ability of a set of features.
What is a redundant feature in machine learning?
Redundant Features Slow Down the Training Process
The more features you have, the slower the calculations are. However, there is another hidden factor that slows down training significantly. Having correlated features in the training set makes the loss landscape ill-conditioned (definition comes later).
Do redundant features affect classifier performance?
Because there are a lot of irrelevant and redundant features in high-dimensional data, these features not only lead to higher computational complexity but also reduce the accuracy and efficiency of classification methods.
