Density estimation: Difference between revisions
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In machine learning, density estimation is defined as an unsupervised learning technique. | In machine learning, density estimation is defined as an unsupervised learning technique. It learns relations among attributes in the data.<ref name="people.cs.pitt">[http://people.cs.pitt.edu/~milos/courses/cs2750-Spring2012/Lectures/class3.pdf Density estimation]</ref> | ||
== Types == | |||
* Parametric density estimation: | |||
* Non-parametric density estimation: | |||
== Terminology == | == Terminology == | ||
Revision as of 21:30, 24 March 2020
In machine learning, density estimation is defined as an unsupervised learning technique. It learns relations among attributes in the data.[1]
Types
- Parametric density estimation:
- Non-parametric density estimation:
Terminology
- Estimator
- Consistent estimator
- Unbiased estimator
- Parametric methods
- Non-parametric methods
- Explicit density estimation
- Implicit density estimation