Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 31 - 40 of 268 for v (0.05 sec)

  1. What’s in the Senate’s version of Trump’s ‘big ...

    Frank Thorp V Frank Thorp V is a producer and off-air...By Julie Tsirkin , Frank Thorp V and Sahil Kapur WASHINGTON — President...
    www.nbcnews.com/politics/congress/trump-big-beautiful-bill-senate-tax-medicaid-cuts-rcna216024
    Sat Jul 05 01:03:15 UTC 2025
      432.7K bytes
      Cache
     
  2. RegressorMixin — scikit-learn 1.7.0 documentation

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html
    Fri Jul 11 17:08:41 UTC 2025
      115.7K bytes
      Cache
     
  3. bootstrap.js

    v=d.y,y=void 0===v?0:v,w="function"==typeof...d 0===_?u:_,v=i.elementContext,y=void 0===v?f:v,w=i.altBoundary,E=void...
    scikit-learn.org/stable/_static/scripts/bootstrap.js
    Fri Jul 11 17:08:42 UTC 2025
      79.8K bytes
     
  4. Bunch — scikit-learn 1.7.0 documentation

    v in E: D[k] = v In either case, this is...
    scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html
    Fri Jul 11 17:08:39 UTC 2025
      118.3K bytes
      Cache
     
  5. BernoulliRBM — scikit-learn 1.7.0 documentation

    gibbs ( v ) [source] # Perform one Gibbs...Gibbs sampling step. Parameters : v ndarray of shape (n_samples, n_features)...
    scikit-learn.org/stable/modules/generated/sklearn.neural_network.BernoulliRBM.html
    Fri Jul 11 17:08:39 UTC 2025
      135.8K bytes
      Cache
     
  6. feature_extraction.rst.txt

    :math:`v_{norm} = \frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 +...:math:`v_{norm} = \frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 +...
    scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt
    Fri Jul 11 17:08:38 UTC 2025
      43.4K bytes
     
  7. TransformedTargetRegressor — scikit-learn 1.7.0...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.compose.TransformedTargetRegressor.html
    Fri Jul 11 17:08:38 UTC 2025
      143.2K bytes
      Cache
     
  8. plot_kmeans_digits.zip

    score compl completeness score v-meas V measure ARI adjusted Rand...metrics.completeness_score, metrics.v_measure_score, metrics.adjusted_rand_score,...
    scikit-learn.org/stable/_downloads/1393861b58df827d4c681b80a5be2472/plot_kmeans_digits.zip
    Fri Jul 11 17:08:39 UTC 2025
      15.5K bytes
     
  9. 2.5. Decomposing signals in components (matrix ...

    V^*) = \underset{U, V}{\operatorname{arg\,min\,}}...we multiply it with \(V_k\) : \[X' = X V_k\] Note Most treatments...
    scikit-learn.org/stable/modules/decomposition.html
    Fri Jul 11 17:08:38 UTC 2025
      126.7K bytes
      Cache
     
  10. OrthogonalMatchingPursuit — scikit-learn 1.7.0 ...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.OrthogonalMatchingPursuit.html
    Fri Jul 11 17:08:39 UTC 2025
      134.2K bytes
      2 views
      Cache
     
Back to top