How to interpret PCA
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Hi, I was trying a principal component analysis and I'd like to get some help
First, here is a table that shows measured concentrations of dopamine (DA), 3,4-hydroxyphenylacetic acid (DOPAC), and homovanillic acid (HVA) in mice urine after 2 hours of brain electric stimulus. The stimulus intensity were control in 3 mice, 100 μA in 4 mice, and 200 μA in 4 mice.
Using pca function, How can I interpret that which hormone is the most significant?
Also, I'd like to draw a scatter plot in different colors in each group (control, 100, 200)?
3 件のコメント
Star Strider
2020 年 9 月 7 日
Jin Woo PARK
2020 年 9 月 7 日
Image Analyst
2020 年 9 月 7 日
You forgot to attach x2hours. Please do so
save('answers.mat', 'x2hours');
Also, I don't know what you plotted but I'm not sure I see any point in using PCA since your data looks like a shotgun blast - totally uncorrelated.
回答 (1 件)
the cyclist
2020 年 9 月 7 日
編集済み: the cyclist
2020 年 12 月 26 日
0 投票
@Jin Woo:
If you search this forum for cyclist and pca, you will find a few question/answers where I explain a lot about the interpretation of PCA output. Here are a couple you might want to look at:
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ヘルプ センター および File Exchange で Dimensionality Reduction and Feature Extraction についてさらに検索
2020 年 9 月 7 日
2020 年 12 月 26 日
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