Created
September 22, 2015 14:35
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For Machine Learning and Web Analytics blogpost http://markedmondson.me/intro-to-machine-learning-with-web-analytics-random-forests-and-k-means
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| ## Finding number of components | |
| pc <- princomp(model_data) | |
| plot(pc, type="l") | |
| # look for dimension that is ~ 85% variance | |
| summary(pc) | |
| loadings(pc) | |
| # run more convenient pca needed for k-means | |
| pc <- prcomp(k_data) | |
| ## Chose top 35 dimensions | |
| ## limit data to first 35 columns | |
| comp <- data.frame(pc$x[,1:35]) |
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