Data Science, Machine Learning, Pca, Big Data, Principal Component.
2). It is also a linear combination of the original features which captures the remaining variance in the dataset such that the correlation between first and second principal component is zero, and thus their directions are orthogonal or perpendicular to each other. Similarly, for d features in our