March 21, 2019
In the context of this project, I applied Principal Component Analysis (PCA) in order to create a model that reduces data dimensions and resises images. Initially, PCA was tested in a 2D dataset, which is shown in Figure1.
Figure 1: 2-dimensional dataset The first step is to compute the principal components of the input data. These components can be seen in Figure 2.
Figure 2: Principal components of 2D dataset Now, input 2D dataset can be projected to the principal components in one dimension, as Figure 3 illustrates.