query: PCA in Matlab: why is the number of PCs always equal to the number of rows/observations minus 1?
positive_passages.docid: 18487
positive_passages.text: Why are there only $n-1$ principal components for $n$ data if the number of dimensions is $\ge n$?
negative_passages.docid: 7603
negative_passages.text: Relationship between SVD and PCA. How to use SVD to perform PCA?
negative_passages.docid: 90064
negative_passages.text: What does it mean when Mathematica returns a zero "eigenvector"?
negative_passages.docid: 154304
negative_passages.text: Do PCA affect different classification methods?
negative_passages.docid: 91989
negative_passages.text: What does the following colon (:) mean in MATLAB syntax?
negative_passages.docid: 112934
negative_passages.text: Is PCA followed by a rotation (such as varimax) still PCA?
negative_passages.docid: 86082
negative_passages.text: Interpreting PCA scores
negative_passages.docid: 61003
negative_passages.text: Why shouldn't the denominator of the covariance estimator be n-2 rather than n-1?
negative_passages.docid: 158823
negative_passages.text: Principal component analysis "backwards": how much variance of the data is explained by a given linear combination of the variables?
negative_passages.docid: 90472
negative_passages.text: Is there a foreach in MATLAB? If so, how does it behave if the underlying data changes?
negative_passages.docid: 49582
negative_passages.text: How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
negative_passages.docid: 14181
negative_passages.text: Can averaging all the variables be seen as a crude form of PCA?
negative_passages.docid: 154261
negative_passages.text: PCA when the dimensionality is greater than the number of samples
negative_passages.docid: 97435
negative_passages.text: Reversing PCA back to the original variables
negative_passages.docid: 45261
negative_passages.text: Why is the determinant of a rotation matrix equal to 1?
negative_passages.docid: 101622
negative_passages.text: Choosing number of principal components to retain
negative_passages.docid: 67557
negative_passages.text: Imputation of missing values for PCA