31. For a second analysis, the scores from both cultures were combined, and principal components analysis was used. 32. This is to be contrasted with principal component analysis which seeks to minimize the mean square error of all residuals. 33. Face images usually occupy a high-dimensional space and conventional principal component analysis was intractable on such data sets. 34. For each area, it learns a separate Principal Component Analysis ( PCA ) basis and reconstructs the area separately. 35. This problem is a shortcoming of principal component analysis in general, not just of M-SSA in particular. 36. Ordinary principal component analysis ( PCA ) uses a vector space transform to reduce multidimensional data sets to lower dimensions. 37. By applying principal component analysis to data from " classical genetic markers " ( protein cline with a Near Eastern focus. 38. Since centered data is required to perform an effective principal component analysis , we'centralize'K to become K' 39. These are then reduced to 10-15 dimensions by principal component analysis , giving the appearance information A \,. 40. Random Project does not perform as well as Principal Component Analysis at preserving inter-point distances but is computationally cheaper.
