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linear_model.rst.txt
Boyd and D. Gorinevsky, in IEEE Journal of...math:: AIC = -2 \log(\hat{L}) + 2 d where :math:`\hat{L}` is the maximum...scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
about.rst.txt
D. and Brucher, M. and Perrot, M....scikit-learn.org/stable/_sources/about.rst.txt -
model_evaluation.rst.txt
D. Kelleher, Brian Mac Namee, Aoife D'Arcy, `Fundamentals...outliers. .. _d2_score: D² score -------- The D² score computes the...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
cross_validation.rst.txt
"d", "d", "d"] >>> groups = [1, 1, 1,...Cross-validation iterators for i.i.d. data ---------- Assuming that...scikit-learn.org/stable/_sources/modules/cross_validation.rst.txt -
index.rst.txt
This example visually compares d..."> .. only:: html .. image::...scikit-learn.org/stable/_sources/auto_examples/index.rst.txt -
feature_extraction.rst.txt
d)}=\text{tf(t,d)} \times \text{idf(t)}`....scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
decomposition.rst.txt
:math:`d \in D`, draw the topic proportions :math:`\theta_d \sim...definitions of :math:`d_{KL}` and :math:`d_{IS}` respectively....scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
clustering.rst.txt
math:: d_m(x_p, x_q) = \max\{d_c(x_p), d_c(x_q), d(x_p, x_q)\}...math:: d_c(x_p)=d(x_p, x_*). Next it defines :math:`d_m(x_p,...scikit-learn.org/stable/_sources/modules/clustering.rst.txt -
neighbors.rst.txt
:math:`D` dimensions, this approach scales as :math:`O[D N^2]`....refers to the dimension :math:`d \le D` of a manifold on which the...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt -
preprocessing.rst.txt
"a" and "d" are considered infrequent and...+ ["b"] * 20 + ["c"] * 10 + ["d"] * 3 + [np.nan]], ... dtype=object).T...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt