Feature Extraction: Pre-determined Features vs. Featureless Deep Learning

Feature Extraction: Pre-determined Features vs. Featureless Deep Learning

Alireza Fereidunian Alireza Fereidunian

Alireza Fereidunian

Lifelong Learner | AProfessor | IEEE SM'19 ■Energy Smart Environments: Grid, City, Home, Harvesting, Transition ■Distribution Automation ■AI & Data Analytics ■Systems ■Reliability ■Complexity ■Automation ■Maintenance

发布日期: 2024年2月17日
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A comparison of the same learning problem using pre-determined features and featureless deep learning, as well as the basic notion of finding the features using a sort of sensitivity analysis in the resulting deep learning artificial neural network is presented as a short essay contribution in a LinkedIn collaborative article at:

https://www.dhirubhai.net/advice/3/what-best-practices-selecting-features-during-nqlbe?contributionUrn=urn%3Ali%3Acomment%3A%28articleSegment%3A%28urn%3Ali%3AlinkedInArticle%3A7161446243909500928%2C7161446246170222592%29%2C7164254414596255744%29&dashContributionUrn=urn%3Ali%3Afsd_comment%3A%287164254414596255744%2Curn%3Ali%3AarticleSegment%3A%28urn%3Ali%3AlinkedInArticle%3A7161446243909500928%2C7161446246170222592%29%29&articleSegmentUrn=urn%3Ali%3AarticleSegment%3A%28urn%3Ali%3AlinkedInArticle%3A7161446243909500928%2C7161446246170222592%29

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