September 2019
Intermediate to advanced
420 pages
10h 29m
English
book
Machine Learning for OpenCV 4 - Second Edition
by Aditya Sharma, Michael Beyeler (USD), Vishwesh Ravi Shrimali, Michael Beyeler
Content preview from Machine Learning for OpenCV 4 - Second Edition
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Implementing independent component analysis (ICA)
Other useful dimensionality reduction techniques that are closely related to PCA are provided by scikit-learn, but not OpenCV. We mention them here for the sake of completeness. ICA performs the same mathematical steps as PCA, but it chooses the components of the decomposition to be as independent as possible from each other, rather than per predictor as in PCA.
In scikit-learn, ICA is available from the decomposition module:
In [9]: from sklearn import decompositionIn [10]: ica = decomposition.FastICA(tol=0.005)
Why do we use tol=0.005? Because we want the FastICA to converge to some particular value. There are two methods to do that—increase the number of iterations (the default value is ...
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