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Results 21 - 30 of 226 for d (0.04 sec)

  1. 1.8. Cross decomposition — scikit-learn 1.4.2 d...

    \(X \in \mathbb{R}^{n \times d}\) and \(Y \in \mathbb{R}^{n \times...compute \(u_k \in \mathbb{R}^d\) and \(v_k \in \mathbb{R}^t\)...
    scikit-learn.org/stable/modules/cross_decomposition.html
    Sat May 18 15:26:00 UTC 2024
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  2. Putting it all together — scikit-learn 1.4.2 do...

    "n_samples: %d " % n_samples ) print ( "n_features: %d " % n_features..."Extracting the top %d eigenfaces from %d faces" % ( n_components...
    scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html
    Sun May 19 20:00:39 UTC 2024
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  3. sklearn.manifold.Isomap — scikit-learn 1.4.2 do...

    frobenius_norm[K(D) - K(D_fit)] / n_samples Where D is the matrix...isomap kernel: K(D) = -0.5 * (I - 1/n_samples) * D^2 * (I - 1/n_samples)...
    scikit-learn.org/stable/modules/generated/sklearn.manifold.Isomap.html
    Sun May 19 20:00:39 UTC 2024
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  4. 4.2. Permutation feature importance — scikit-le...

    dataset (training or validation) \(D\) . Compute the reference score...of the model \(m\) on data \(D\) (for instance the accuracy for...
    scikit-learn.org/stable/modules/permutation_importance.html
    Sat May 18 15:26:00 UTC 2024
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  5. 2.2. Manifold learning — scikit-learn 1.4.2 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
    Sun May 19 20:00:39 UTC 2024
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  6. 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
    Sun May 19 01:07:54 UTC 2024
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  7. sklearn.linear_model.GammaRegressor — scikit-le...

    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
    Sun May 19 20:00:39 UTC 2024
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  8. sklearn.linear_model.TweedieRegressor — scikit-...

    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
    Sun May 19 20:00:39 UTC 2024
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  9. 1.7. Gaussian Processes — scikit-learn 1.4.2 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
    Sun May 19 20:00:39 UTC 2024
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  10. sklearn.linear_model.PoissonRegressor — scikit-...

    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.PoissonRegressor.html
    Sun May 19 20:00:39 UTC 2024
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