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- 1Goal of PCAGoal is to reduce the dimensionality of the data while retaining as much possible of the variation present in the datasheet
- 2Objective of PCArigdly rotate the axes of this p-dimenstional space to new positions
- 3Eigenvaluea number telling you how much variance there in the data in that direction
- 4Indepentent component analysis(ICA) conceptA given signal is generated by linear mixing of independent components. ICA is a statistical analysis method to estiimate those components and mixing rule
- 5Whiten dataremove any correlations in the data
- 6Watershed segmentation basicseach grayscale image can be considered as a topograpic map(depth, map, terrain
) - 7what is watershed segmentation sensetive to?noise
- 8watershed segmentation with markersthe effort to provide over segmentation
- 9CNN aimreduce number of training samples
- 10which samples are kept after CNN?the samples that are needed to define the decision boundry
- 11when is SMOTE used?when one class in the training set dominates the other
- 12DTW basicsalgorithm to measure similarity between two sequences that vary in time or speed
- 13when are Eculidean distance used in DTWwhen we have extended the sequences (X' and Y')
- 14DTW restrictions?The path should not go down or to the left. No element should be skipped in a sequence
- 15how does the the points devides to cells in kNNA Voronoi diagram
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- Karteikarten am Ohne Titel, erstellt von asd asd am 11/02/2019.
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