PCA clearly explained - StatQuest!!!
statquest.org
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Update: A lot of people ask to see example code that shows how to actually do PCA. Here’s how to do it in R [sourcecode language=”R”] ## In this example, the data is in a matrix called ## data.matrix ## columns are individual samples (i.e. cells) ## rows are measurements taken for all the samples […]
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SOLVED: 1) Load the iris sample dataset into Python using a Pandasdataframe. Perform a PCA using the Scikit Decomposition component,and provide the percentage of variance explained by each of thePrincipal Components. Compare this to the percentage of varianceexplained by each of the original features. What do youobserve?2) Use Matplotlib to plot a projection of each feature onto the1st Principal Component from the above problem against theoriginal feature itself. Which pair of features show a cl
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