deepak panday
Last seen: Today
2 total contributions since 2017deepak panday's Badges
Download any 10 unique submissions
Awarded to deepak panday on 01 Feb 2020
Publish your first comment or rating
Awarded to deepak panday on 09 Oct 2019
Answer 1 question that was unanswered for more than 30 days
Awarded to deepak panday on 20 Jul 2017
Provide your first answer ever to someone else's question
Awarded to deepak panday on 20 Jul 2017
Answered
Principal Component Analysis for feature extraction
[coff,score]=pca(data) newData = data*coff(:,1:n) where n is number of feature to selected.
Principal Component Analysis for feature extraction
[coff,score]=pca(data) newData = data*coff(:,1:n) where n is number of feature to selected.
casi 3 años ago | 1
Answered
Need high dimension (30-50) dataset for applying PCA
google UCI machine learning datasets.
Need high dimension (30-50) dataset for applying PCA
google UCI machine learning datasets.
más de 3 años ago | 0
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
Select web siteYou can also select a web site from the following list:
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)