Feature Selection

Feature Engineering and Feature Selection with Python: A Practical Guide For Feature Crafting

Feature Engineering and Feature Selection with Python: A Practical Guide For Feature Crafting
English | 2021 | ASIN: B09FP54PCN | 253 Pages | PDF EPUB | 12 MB

Linear Algebra And Feature Selection In Python  eBooks & eLearning

Posted by ELK1nG at Feb. 11, 2023
Linear Algebra And Feature Selection In Python

Linear Algebra And Feature Selection In Python
Last updated 3/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.03 GB | Duration: 2h 54m

Acquire the Theoretical and Practical Foundations That Would Allow You to Learn Machine Learning With Understanding

Feature Selection for Knowledge Discovery and Data Mining  eBooks & eLearning

Posted by insetes at Feb. 25, 2019
Feature Selection for Knowledge Discovery and Data Mining

Feature Selection for Knowledge Discovery and Data Mining By Huan Liu, Hiroshi Motoda (auth.)
1998 | 214 Pages | ISBN: 1461376041 | PDF | 13 MB
New Theory of Discriminant Analysis After R. Fisher: Advanced Research by the Feature Selection Method for Microarray Data

New Theory of Discriminant Analysis After R. Fisher: Advanced Research by the Feature Selection Method for Microarray Data by Shuichi Shinmura
English | 2016 | ISBN: 9811021635 | 208 Pages | PDF | 4.29 MB
Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint (Repost)

Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint by Mark K. Hinders
English | EPUB | 2020 | 353 Pages | ISBN : 3030493946 | 109.8 MB

This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means.
Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint (Repost)

Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint by Mark K. Hinders
English | EPUB | 2020 | 353 Pages | ISBN : 3030493946 | 109.8 MB

This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means.
The Naïve Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection

T. Hristea, Florentina T., "The Naïve Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection "
English | ISBN: 3642336922 | 2013 | 84 pages | EPUB, PDF | 509 KB + 1468 KB
Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint (Repost)

Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint by Mark K. Hinders
English | EPUB | 2020 | 353 Pages | ISBN : 3030493946 | 109.8 MB

This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means.
Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint

Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint by Mark K. Hinders
English | PDF,EPUB | 2020 | 353 Pages | ISBN : 3030493946 | 133.1 MB

This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means.
Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations (repost)

Oleg Okun, "Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations"
English | 2011 | ISBN: 1609605578 | 445 pages | PDF | 4,8 MB

Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations offers a unique perspective on machine learning aspects of microarray gene expression based cancer classification.