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Search results for “функции потерь”

63 results

Machine Learning 1. Lecture 13. Clustering and Semi-Supervised Learning

2026LectureКонстантин Вячеславович Воронцов

The clustering problem and its ill-posedness, the aims of clustering, types of cluster structure, sensitivity to the choice of metric; the problem of semi-supervised learning and transductive learning, why it reduces neither to classification nor to clustering; criteria of clustering quality, the silhouette coefficient, the BCubed measures of precision and recall; the k-means method (Lloyd's algorithm) as a simplification of the EM algorithm for a mixture of Gaussians; the DBSCAN algorithm; agglomerative hierarchical clustering, the Lance–Williams formula and its special cases, the dendrogram, monotonicity, contracting and dilating distances, Ward's distance; semi-supervised learning based on classification: self-training, co-training, co-learning, the transductive SVM, expectation regularisation (XR).
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280

Алгебра 1, Листок 1

2026Problem sheetAlexey Ilyin

Задачные листки к курсам алгебры. Институт и учебное заведение в исходных публикациях не указаны, поэтому здесь не названы.
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180

Теория вероятностей, Листок 1

2026Problem sheetСтанислав Шапошников

Задачный листок к курсу теории вероятностей. Институт и учебное заведение в исходных публикациях не указаны, поэтому здесь не названы.
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270

Евклидовы пространства

2026LectureTaras Panov

Евклидовы и эрмитовы пространства, скалярное произведение, неравенство Коши–Буняковского и неравенство треугольника, ортогональные системы векторов.
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190

Линейные пространства

2026LectureTaras Panov

Линейные пространства над произвольным полем, подпространства, линейная зависимость, базис и размерность, сумма и пересечение подпространств, замена базиса.
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530

Mathematical Analysis 1. Lecture 1

2026LectureСтанислав Шапошников

Naive set theory and Russell's paradox, Kuratowski's ordered pair and the Cartesian product, a function as a subset of a product, composition, injections, surjections and bijections, the group of bijections and the embedding of any group into it, equinumerosity and indicator functions, the Cantor–Bernstein and Cantor theorems.
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290

Integrals of Rational Functions

2026ReferenceSergey

Reference table of indefinite integrals of rational functions, including quadratic denominators and partial-fraction forms.
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290

Machine Learning 2. Lecture 8. Association Rule Mining

2026LectureКонстантин Вячеславович Воронцов

Association rule mining as unsupervised learning: binary features, support and frequent itemsets, the association rule, minimum support MinSupp and minimum confidence MinConf; market basket analysis; the link between association rules and logical regularities; the anti-monotonicity of support; the APriori algorithm: breadth-first search for frequent itemsets and recursive extraction of rules; modifications: search on a random subsample, item hierarchies, incremental and decremental algorithms; the FP-growth algorithm: the prefix FP-tree, building it in one pass over the transaction database, computing the support of any itemset from the tree, the conditional FP-tree and recursive search for frequent itemsets; the speed of FP-growth compared with APriori.
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160

Probability Theory. Lecture 1

2026LectureСтанислав Шапошников

The finite probability space and five properties of probability, a description of all probability measures on a finite set, equally likely outcomes and the choice of a model, classical paradoxes (two dice, the division of the stakes, Bertrand's paradox), conditional probability and the product rule, the law of total probability as a way to define a measure, Bayes' formula, independence of events.
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170