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1.10. Decision Trees — scikit-learn 1.4.2 docum...
dataset \(D\) is defined as follows: \[\mathrm{LL}(D, T) = -\frac{1}{n}...y_i) \in D} \sum_k I(y_i = k) \log(T_k(x_i))\] where \(D\) is a...scikit-learn.org/stable/modules/tree.html -
1.2. Linear and Quadratic Discriminant Analysis...
training sample \(x \in \mathcal{R}^d\) : \[P(y=k | x) = \frac{P(x |...\[P(x | y=k) = \frac{1}{(2\pi)^{d/2} |\Sigma_k|^{1/2}}\exp\left(-\frac{1}{2}...scikit-learn.org/stable/modules/lda_qda.html -
sklearn.gaussian_process.kernels.DotProduct — s...
coefficients of \(x_d (d = 1, . . . , D)\) and a prior of \(N(0,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.DotProduct.html -
sklearn.cluster.HDBSCAN — scikit-learn 1.4.2 do...
D., & Sander, J. Density-based clustering...2 ] Campello, R. J., Moulavi, D., Zimek, A., & Sander, J. Hierarchical...scikit-learn.org/stable/modules/generated/sklearn.cluster.HDBSCAN.html -
sklearn.preprocessing.OrdinalEncoder — scikit-l...
“a” and “d” are considered infrequent and..."b" ] * 20 + [ "c" ] * 10 + [ "d" ] * 3 + [ np . nan ]], ... dtype...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html -
sklearn.gaussian_process.kernels.RationalQuadra...
x_j) = \left( 1 + \frac{d(x_i, x_j)^2 }{ 2\alpha l^2}\right)^{-\alpha}\]...length scale of the kernel and \(d(\cdot,\cdot)\) is the Euclidean...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RationalQuadratic.html -
sklearn.gaussian_process.kernels.ExpSineSquared...
\text{exp}\left(- \frac{ 2\sin^2(\pi d(x_i, x_j)/p) }{ l^ 2} \right)\]...periodicity of the kernel and \(d(\cdot,\cdot)\) is the Euclidean...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ExpSineSquared.html -
MetaTalk
D&D (and GURPS!) master gamer, funny,...site that could use it. I know I'd find it useful, anyway. posted...metatalk.metafilter.com -
Statistical learning: the setting and the estim...
takes a dataset (usually a 2-d array): >>> estimator . fit (...scikit-learn.org/stable/tutorial/statistical_inference/settings.html -
sklearn.gaussian_process.kernels.RBF — scikit-l...
x_j) = \exp\left(- \frac{d(x_i, x_j)^2}{2l^2} \right)\] where...length scale of the kernel and \(d(\cdot,\cdot)\) is the Euclidean...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RBF.html