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clustering.rst.txt
\sum_{q=1}^k n_q (c_q - c_E) (c_q - c_E)^T with :math:`C_q` the set...math:: C = \left[\begin{matrix} C_{00} & C_{01} \\ C_{10} & C_{11}...scikit-learn.org/stable/_sources/modules/clustering.rst.txt -
confusion_matrix — scikit-learn 1.5.0 documenta...
a confusion matrix \(C\) is such that \(C_{i, j}\) is equal to...negatives is \(C_{0,0}\) , false negatives is \(C_{1,0}\) , true...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
SVR — scikit-learn 1.5.0 documentation
C = 1.0 , epsilon = 0.1 , shrinking...free parameters in the model are C and epsilon. The implementation...scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html -
6.7. Kernel Approximation — scikit-learn 1.5.0 ...
\prod_i \frac{2\sqrt{x_i+c}\sqrt{y_i+c}}{x_i + y_i + 2c}\] It has...kernels” Li, F., Ionescu, C., and Sminchisescu, C. - Pattern Recognition,...scikit-learn.org/stable/modules/kernel_approximation.html -
LogisticRegressionCV — scikit-learn 1.5.0 docum...
the best C is the average of the C’s that correspond...folds, and the coefs and the C that corresponds to the best score...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html -
pydata-sphinx-theme.js
then((e=>{c[t]=e,r(a)}),(e=>{c[n]=e,r(a)}));var c={};return c[e]=e=>e(a),c}}var....r--?e.r++:e())))},c.a=(o,a,c)=>{var i;c&&((i=[]).d=-1);var d,s,l,u=new...scikit-learn.org/stable/_static/scripts/pydata-sphinx-theme.js -
MultinomialNB — scikit-learn 1.5.0 documentation
References C.D. Manning, P. Raghavan and H....The input samples. Returns : C ndarray of shape (n_samples,)...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html -
CalibratedClassifierCV — scikit-learn 1.5.0 doc...
Zadrozny & C. Elkan, ICML 2001 [ 2 ] Transforming...Probability Estimates, B. Zadrozny & C. Elkan, (KDD 2002) [ 3 ] Probabilistic...scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibratedClassifierCV.html -
3.1. Cross-validation: evaluating estimator per...
"c" , "c" , "c" , "d" , "d" , "d" ] >>>..."a" , "b" , "b" , "b" , "c" , "c" , "c" , "a" ] >>> groups = [...scikit-learn.org/stable/modules/cross_validation.html -
HuberRegressor — scikit-learn 1.5.0 documentation
the samples where |(y - Xw - c) / sigma| < epsilon and the absolute...the samples where |(y - Xw - c) / sigma| > epsilon , where the...scikit-learn.org/stable/modules/generated/sklearn.linear_model.HuberRegressor.html