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We compare both, a PCA based method against an alternative method based on an Artificial Neural Networks model.
The PCA based method fails.
The PCA based method fails for all three examples.
The PCA based method fails for this example.
The PCA based method does not lead to an identifiable method.
Due to this result, we consider the PCA based method to have failed.
Similar(34)
As a popular linear approach in dimension reduction, principal component analysis (PCA) based methods have been applied for pathway based GWAS [ 13, 19].
For initial statistical analysis, the data were first subjected to Principal Component Analysis (PCA, based on the method of [ 84]) and hierarchical clustering analysis to compare the gene expression patterns of the arrays in terms of our classification.
Principal component analysis (PCA) based pattern matching methods have been applied to process monitoring and fault detection.
This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based.
Two families of PCA based combustion model were recently developed: score-PCA and MG-PCA.
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