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Feature selection for best mean square approximation of class densities
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Peters, C. |
| Copyright Year | 1978 |
| Description | A criterion for linear feature selection is proposed which is based on mean square apporximation of class density functions. It is shown that for the widest possible class of approximants, the criterion reduces to Devijver's Bayesian distance. For linear approximants the criterion is equivalent to well known generalized Fisher criteria. |
| File Size | 749479 |
| Page Count | 13 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19780022945 |
| Archival Resource Key | ark:/13960/t6p02zw90 |
| Language | English |
| Publisher Date | 1978-07-01 |
| Access Restriction | Open |
| Subject Keyword | Statistics And Probability Linear Systems Approximation Least Squares Method Pattern Recognition Distribution Property Functions Mathematics Density Distribution Bayes Theorem Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
