November 2019
Intermediate to advanced
346 pages
9h 36m
English
We begin by reading in our dataset and then standardizing it, as in the recipe on standardizing data (steps 1 and 2). (It is necessary to work with standardized data before applying PCA). We now instantiate a new PCA transformer instance, and use it to both learn the transformation (fit) and also apply the transform to the dataset, using fit_transform (step 3). In step 4, we analyze our transformation. In particular, note that the elements of pca.explained_variance_ratio_ indicate how much of the variance is accounted for in each direction. The sum is 1, indicating that all the variance is accounted for if we consider the full space in which the data lives. However, just by taking the first few directions, we can account for ...