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sportscidata.com | ||
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poissonisfish.com
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| | | | | My last entryintroduces principal component analysis (PCA), one of many unsupervised learning tools. I concluded the post with a demonstration of principal component regression (PCR), which essentially is a ordinary least squares (OLS) fit using the first $latex k &s=1$ principal components (PCs) from the predictors. This brings about many advantages: There is virtually no... | |
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algobeans.com
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| | | | | You are exploring the nutritional content of food. How can food items be differentiated? How might they be classified? PCA derives underlying variables that help you slice your data for these insights. | |
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dm13450.github.io
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| | | | | Principal component analysis (PCA) reduces a dataset to its main components. When we apply it to a dataset of different currencies it helps us understand how each currency drives the overall portfolio and what currency might be a common factor. | |
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blog.demofox.org
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| | | In the last post, I talked about imaginary numbers, complex numbers, and how to use them to rotate vectors in 2d. In this post, I want to share another interesting type of number called a "Dual Number" that uses the symbol ? (epsilon) and has a neat trick of automatically calculating the derivative of a... | ||
