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Machine learning

#machine-learning · 80 entries. Projects, essays and notes, newest first. Page 3 of 4.

02-02-458Beta-Binomial Conjugacy PosteriorNoteModel selection and information criteria 02-02-459Posterior OddsNoteModel selection and information criteria 02-02-460Generative ModelNoteProbabilistic PCA (PPCA)02-02-461Latent Variable PriorNoteProbabilistic PCA (PPCA)02-02-462Marginal LikelihoodNoteProbabilistic PCA (PPCA)02-02-463PPCA MLE ParametersNoteProbabilistic PCA (PPCA)02-02-464Hard Margin OptimizationNoteSupport vector machines (SVM) and classification 02-02-465Hinge Loss FunctionNoteSupport vector machines (SVM) and classification 02-02-466Hypothesis FunctionNoteSupport vector machines (SVM) and classification 02-02-467Soft Margin Optimization (Primal)NoteSupport vector machines (SVM) and classification 02-02-468Subject toNoteSupport vector machines (SVM) and classification 02-02-469Unconstrained Hinge FormulationNoteSupport vector machines (SVM) and classification 02-02-470Gini Impurity (CART)NoteTree-based models and ensembles 02-02-471Information Gain, ID3/C4.5NoteTree-based models and ensembles 02-02-477Bayes Factor (Model Comparison)NoteEmpirical risk and its minimisation 02-02-478Empirical RiskNoteEmpirical risk and its minimisation 02-02-479Expected (True) RiskNoteEmpirical risk and its minimisation 02-02-480Linear PredictorNoteEmpirical risk and its minimisation 02-02-481Maximum A Posteriori, MAPNoteEmpirical risk and its minimisation 02-02-482Negative Log-LikelihoodNoteEmpirical risk and its minimisation 02-02-483Nested Cross-ValidationNoteModel selection and cross-validation 02-02-485Conjugate PriorNoteThe exponential family 02-02-486General FormNoteThe exponential family 02-02-487Bipartite GraphNoteGraph foundations and the Laplace matrix