How to use classification after PCA(dimensionality reduction)
显示 更早的评论
Hello.
I want to classify videos.
The original data : 25290 x 25
After applying dimensionality reduction like PCA, I got this data.
The reduced data : 2 x 25
Is it resonable to use these reduced data for classification?
I got low accuracy of classification. Could you give some ideas to solve it?
采纳的回答
Shishir Singhal
2020-4-9
0 个投票
Don't use PCA for dimentionality reduction or feature selection in case of videos or images. Instead use some feature extraction techniques in images like HOG features, sift features, optical flow(for videos), etc. Since the datapoints are very less(assuming 25 datapoints), you could use some data augementation techniques for videos.
For example, crop some random sequence from the video for temporal augmentation then use Image augmentation for each frame.
For Image augmentation, you can refer to documentation here: https://www.mathworks.com/help/deeplearning/ref/imagedataaugmenter.html
Hope it helps !!! :)
更多回答（0 个）
类别
在 帮助中心 和 File Exchange 中查找有关 Dimensionality Reduction and Feature Extraction 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
