Selection Of Informative Features using The Modified Version Of The Delta Method | Zendy

Mamatov Narzillo | Zendy; Niyozmatova Nilufar | Zendy; Abdurashid Samijonov | Zendy; Yuldashev Zafar | Zendy; Dadakhanov Musokhon | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Selection Of Informative Features using The Modified Version Of The Delta Method

Author(s) -

Mamatov Narzillo,

Niyozmatova Nilufar,

Abdurashid Samijonov,

Yuldashev Zafar,

Dadakhanov Musokhon

Publication year - 2019

Publication title -

international journal of innovative technology and exploring engineering

Language(s) - English

Resource type - Journals

ISSN - 2278-3075

DOI - 10.35940/ijitee.b6590.129219

Subject(s) - heuristic , selection (genetic algorithm) , artificial intelligence , computer science , pattern recognition (psychology) , compact space , machine learning , mathematics , pure mathematics

Currently, the most common criteria for informative features are heuristic criteria related to assessing the separability of given classes and based on the compactness hypothesis fundamental in pattern recognition: with increasing distance between classes, their separability improves. “Good” are those signs that maximize this distance.Although heuristic criteria, although they are widely used in solving practical problems of classification, however, in theoretical terms they are little studied.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research