摘要:
The K-means algorithm is based on the use of squared Euclidean distance as the measure of dissimilarity between a data point and a prototype vector. O 阅读全文
摘要:
To summarize, principal component analysis involves evaluating the mean x and the covariance matrix S of the data set and then finding the M eigenvect 阅读全文
摘要:
Thus we see that there are very close similarities between this Bayesian viewpoint and the conventional one based on error function minimization and r 阅读全文