Hinge Loss

Protected: Discriminant Conformal Losses in Multi-Valued Discriminant by Statistical Mathematics Theory and its Application to Various Loss Functions

Discriminant conformal loss of multi-valued discriminant and its application to various loss functions by statistical mathematics theory utilized in digital transformation, artificial intelligence, and machine learning tasks discriminant model loss, discriminant conformal, narrow order preserving properties, logistic model, maximum likelihood estimation, nonnegative convex function, one-to-other loss, constrained comparison loss, convex nonnegative-valued functions, hinge loss, pairwise comparison loss, multivalued surport vector machine, monotone nonincreasing function, predictive discriminant error, predictive ψ-loss, measurable function

2023.04.04

アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Overview of C-Support Vector Machines by Statistical Mathematics Theory

Support vector machines based on statistical mathematics theory used in digital transformation, artificial intelligence, and machine learning tasks C-support vector machines (support vector ratio, Markov's inequality, probability inequality, prediction discriminant error, one-out-of-two cross checking method, LOOCV, the discriminant, complementarity condition, main problem, dual problem, optimal solution, first order convex optimization problem, discriminant boundary, discriminant function, Lagrangian function, limit condition, Slater constraint assumption, minimax theorem, Gram matrix, hinge loss, margin loss, convex function, Bayes error, regularization parameter)

2023.02.09

アルゴリズム:Algorithmsスパースモデリング幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Overview of Discriminant Adaptive Losses in Statistical Mathematics Theory

Overview of Discriminant Conformal Losses in Statistical Mathematics Theory (Ramp Losses, Convex Margin Losses, Nonconvex Φ-Margin Losses, Discriminant Conformal, Robust Support Vector Machines, Discriminant Conformity Theorems, L2-Support Vector Machines, Squared Hinge Loss, Logistic Loss, Hinge Loss, Boosting, Exponential Losses, Discriminant Conformity Theorems for Convex Margin Losses, Bayes Rules, Prediction Φ-loss, Prediction Discriminant Error, Monotonic Nonincreasing Convex Function, Empirical Φ-loss, Empirical Discriminant Error)

2022.12.08

アルゴリズム:Algorithms微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra集合論:Set theory