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1.6. Nearest Neighbors — scikit-learn 1.5.0 doc...
samples in \(D\) dimensions, this approach scales as \(O[D N^2]\) ....approximately \(O[D \log(N)]\) KD tree query time changes with \(D\) in a...scikit-learn.org/stable/modules/neighbors.html -
2.2. Manifold learning — scikit-learn 1.5.0 doc...
is \(O[D \log(k) N \log(N)] + O[D N k^3] + O[N d^6] + O[d N^2]\)...is \(O[D \log(k) N \log(N)] + O[D N k^3] + O[k^2 d] + O[d N^2]\)...scikit-learn.org/stable/modules/manifold.html -
GammaRegressor — scikit-learn 1.5.0 documentation
D^2 is defined as \(D^2 = 1-\frac{D(y_{true},y_{pred})}{D_{null}}\)...Compute D^2, the percentage of deviance explained. D^2 is a generalization...scikit-learn.org/stable/modules/generated/sklearn.linear_model.GammaRegressor.html -
TweedieRegressor — scikit-learn 1.5.0 documenta...
D^2 is defined as \(D^2 = 1-\frac{D(y_{true},y_{pred})}{D_{null}}\)...Compute D^2, the percentage of deviance explained. D^2 is a generalization...scikit-learn.org/stable/modules/generated/sklearn.linear_model.TweedieRegressor.html -
1.7. Gaussian Processes — scikit-learn 1.5.0 do...
coefficients of \(x_d (d = 1, . . . , D)\) and a prior of \(N(0,...\text{exp}\left(- \frac{d(x_i, x_j)^2}{2l^2} \right)\] where \(d(\cdot, \cdot)\)...scikit-learn.org/stable/modules/gaussian_process.html -
GitHub - codelibs/fess-testdata: Test Data Repo...
on color-fg-success d-none m-2"> <path d="M13.78 4.22a.75.75...js-clipboard-check-icon color-fg-success d-none"> <path d="M13.78 4.22a.75.75 0...github.com/codelibs/fess-testdata -
Accelerating Elastic detection tradecraft with ...
to share how our internal AI R&D efforts have increased the productivity...plans to pursue further LLM R&D and decided to tackle one of our...www.elastic.co/security-labs/accelerating-elastic-detection-tradecraft-with-llms -
make_sparse_coded_signal — scikit-learn 1.5.0 d...
D and X such that Y = XD where X...shape (n_samples, n_components) , D is of shape (n_components, n_features)...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_coded_signal.html -
DictVectorizer — scikit-learn 1.5.0 documentation
DictVectorizer ( sparse = False ) >>> D = [{ 'foo' : 1 , 'bar' : 2 },...}] >>> X = v . fit_transform ( D ) >>> X array([[2., 0., 1.], [0.,...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html -
Introducing Scalar Quantization in Lucene — Ela...
a n t i z e d @ 15 quantized@15 q u an t i ze d @15 . Figure...vector storage file. Takes up d i m e n s i o n ∗ 4 ∗ n u m V...www.elastic.co/search-labs/blog/scalar-quantization-in-lucene