Pca built-in function and how its works?
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Can anyone tell me the pca built-in function for machine learning also which one dataset are used for dimensionality reduction... Thnx in advance
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KSSV
2019-5-24
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REad abut Singula Value DEcomposition. svd . And refer this for more clarity:
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Muhammad Ibrar
2019-5-24
KSSV
2019-5-24
Matrices...a 2D matrix. Check the documentation..you got many examples: https://in.mathworks.com/help/stats/pca.html
Muhammad Ibrar
2019-5-24
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Steven Lord
2019-5-24
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The books and papers listed in the References section on the documentation page for the pca function in Statistics and Machine Learning Toolbox may be of interest if you want to know the technical details behind principal component analysis. The page linked as the second entry in the Topics section of that page gives a brief overview of what PCA is.
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Muhammad Ibrar
2019-5-24
Steven Lord
2019-5-24
The main point behind PCA is that you use it to analyze your data to identify your data's principal components and learn more about your data.
If you want a sample dataset to experiment with pca you could use rand, randn, randi, gallery, ones, zeros, eye, etc. Some of those would make for more interesting experiments than others.
Muhammad Ibrar
2019-5-24
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