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load_digits — scikit-learn 1.5.2 documentation
Gallery examples: Release Highlights for scikit-learn 1.3 Recognizing hand-written digits A demo of K-Means clustering on the handwritten digits data Feature agglomeration Various Agglomerative Clu...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html -
Digits Classification Exercise — scikit-learn 1...
A tutorial exercise regarding the use of classification techniques on the Digits dataset. This exercise is used in the clf_tut part of the supervised_learning_tut section of the stat_learn_tut_inde...scikit-learn.org/stable/auto_examples/exercises/plot_digits_classification_exercise.html -
Support Vector Machines — scikit-learn 1.5.2 do...
Examples concerning the sklearn.svm module. One-class SVM with non-linear kernel (RBF) Plot classification boundaries with different SVM Kernels Plot different SVM classifiers in the iris dataset P...scikit-learn.org/stable/auto_examples/svm/index.html -
Missing Value Imputation — scikit-learn 1.5.2 d...
Examples concerning the sklearn.impute module. Imputing missing values before building an estimator Imputing missing values with variants of IterativeImputerscikit-learn.org/stable/auto_examples/impute/index.html -
permutation_importance — scikit-learn 1.5.2 doc...
Gallery examples: Release Highlights for scikit-learn 0.22 Feature importances with a forest of trees Gradient Boosting regression Pixel importances with a parallel forest of trees Permutation Impo...scikit-learn.org/stable/modules/generated/sklearn.inspection.permutation_importance.html -
Kernel Density Estimation — scikit-learn 1.5.2 ...
This example shows how kernel density estimation (KDE), a powerful non-parametric density estimation technique, can be used to learn a generative model for a dataset. With this generative model in ...scikit-learn.org/stable/auto_examples/neighbors/plot_digits_kde_sampling.html -
sklearn.preprocessing — scikit-learn 1.5.2 docu...
Methods for scaling, centering, normalization, binarization, and more. User guide. See the Preprocessing data section for further details.scikit-learn.org/stable/api/sklearn.preprocessing.html -
6.5. Unsupervised dimensionality reduction — sc...
2. Random projections # The module:...scikit-learn.org/stable/modules/unsupervised_reduction.html -
Government has clawed back more than $2.5B give...
veterans have returned more than $2.5 billion so far, with about $364...disability payment of more than $2,400 until he returned his separation...www.nbcnews.com/news/us-news/government-clawed-back-25-billion-veterans-got-leave-military-data-s... -
Receiver Operating Characteristic (ROC) with cr...
= 2 ], y [ y != 2 ] n_samples , n_features...linearly separable from the other 2; the latter are not linearly separable...scikit-learn.org/stable/auto_examples/model_selection/plot_roc_crossval.html