Large Datasets
In practice, a large data set leads to a large K, and storing K may become a problem. One way to deal with this is to perform clustering on your large dataset, and populate the kernel with the means of those clusters. Since even this method may yield a relatively large K, it is common to compute only the top P eigenvalues and eigenvectors of K.
Read more about this topic: Kernel Principal Component Analysis
Famous quotes containing the word large:
“A large tree may have some withered twigs; a large family may have some ne’er-do-well offspring.”
—Chinese proverb.