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Pca built-in function and how its works?

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Muhammad Ibrar
Muhammad Ibrar 2019-5-24
评论： Muhammad Ibrar 2019-5-24
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
KSSV 2019-5-24
REad abut Singula Value DEcomposition. svd . And refer this for more clarity:
http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf

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Steven Lord
Steven Lord 2019-5-24
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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Steven Lord
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
Muhammad Ibrar 2019-5-24
Can u send some example of 1 dataset plz actually im new to implement this

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