فارسی
1
برق و الکترونیک::
تجزیه مقدار تکین
Luckily, there is a standard matrix factorization technique called Singular Value Decomposition (SVD) that can decompose the training set matrix X into the dot product of three matrices U
The following Python code uses NumPy's svd() function to obtain all the principal components of the training set, then extracts the first two PCs:
Scikit-Learn's PCA class implements PCA using SVD decomposition just like we did before.
One problem with the preceding implementation of PCA is that it requires the whole training set to fit in memory in order for the SVD algorithm to run.
rnd_pca = PCA(n_components=154, svd_solver="randomized") X_reduced = rnd_pca.fit_transform(X_mnist)
واژگان شبکه مترجمین ایران
2
عمومی::
تجزیه مقدار تكین
شبکه مترجمین ایران
3
روان شناسی و مشاوره::
تجزیه مقدار منفرد
the context of big data sets: singular value decomposition (SVD), representing
Singular value decomposition
SVD is a popular dimensionality-reduction technique similar to principal component
SVD performed on a centered matrix
is equivalent to PCA, and thus PCA can be considered a special case of SVD.
واژگان شبکه مترجمین ایران