Classification algorithms | Dimension reduction | Data mining
Multifactor dimensionality reduction (MDR) is a statistical approach, also used in machine learning automatic approaches, for detecting and characterizing combinations of attributes or independent variables that interact to influence a dependent or class variable. MDR was designed specifically to identify nonadditive interactions among discrete variables that influence a binary outcome and is considered a nonparametric and model-free alternative to traditional statistical methods such as logistic regression. The basis of the MDR method is a constructive induction or feature engineering algorithm that converts two or more variables or attributes to a single attribute. This process of constructing a new attribute changes the representation space of the data. The end goal is to create or discover a representation that facilitates the detection of nonlinear or nonadditive interactions among the attributes such that prediction of the class variable is improved over that of the original representation of the data. (Wikipedia).
Luca Giorgetti: "Distortion for II_1 multifactor inclusions and bimodules"
Actions of Tensor Categories on C*-algebras 2021 "Distortion for II_1 multifactor inclusions and bimodules" Luca Giorgetti - Università degli Studi di Roma "Tor Vergata" Abstract: We introduce an invariant, called distortion, for inclusions of II_1 von Neumann algebras with finite index
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CIRM VIRTUAL CONFERENCE Recorded during the meeting " Diophantine Problems, Determinism and Randomness" the November 24, 2020 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide
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From playlist Solve Multi-Step Equations......Help!
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From playlist Bitcoin Q&A
How to solve a multi step equation with fractions
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From playlist How to Solve Multi Step Equations with Variables on Both Sides
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From playlist How to Solve Multi Step Equations with Variables on Both Sides
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From playlist How to Solve Multi Step Equations with Variables on Both Sides
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From playlist Tutorials
The code is accesible at https://github.com/sepinouda/Machine-Learning
From playlist Machine Learning Course
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DDPS | Model reduction with adaptive enrichment for large scale PDE constrained optimization
Talk Abstract Projection based model order reduction has become a mature technique for simulation of large classes of parameterized systems. However, several challenges remain for problems where the solution manifold of the parameterized system cannot be well approximated by linear subspa
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Recording during the thematic meeting "Non Linear Functional Analysis" the March 7, 2018 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Ma
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