Statistics
0 Questions
2 Answers
RANK
19.689
of 300.338
REPUTATION
2
CONTRIBUTIONS
0 Questions
2 Answers
ANSWER ACCEPTANCE
0.00%
VOTES RECEIVED
1
RANK
of 20.922
REPUTATION
N/A
AVERAGE RATING
0.00
CONTRIBUTIONS
0 Files
DOWNLOADS
0
ALL TIME DOWNLOADS
0
RANK
of 168.149
CONTRIBUTIONS
0 Problems
0 Solutions
SCORE
0
NUMBER OF BADGES
0
CONTRIBUTIONS
0 Posts
CONTRIBUTIONS
0 Public Channels
AVERAGE RATING
CONTRIBUTIONS
0 Highlights
AVERAGE NO. OF LIKES
Feeds
Principal Component Analysis for feature extraction
[coff,score]=pca(data) newData = data*coff(:,1:n) where n is number of feature to selected.
bijna 8 jaar ago | 1
Need high dimension (30-50) dataset for applying PCA
google UCI machine learning datasets.
meer dan 8 jaar ago | 0
