Classification algorithms

Information fuzzy networks

Information fuzzy networks (IFN) is a greedy machine learning algorithm for supervised learning.The data structure produced by the learning algorithm is also called Info Fuzzy Network.IFN construction is quite similar to decision trees' construction.However, IFN constructs a directed graph and not a tree.IFN also uses the conditional mutual information metric in order to choose features during the construction stage while decision trees usually use other metrics like entropy or gini. (Wikipedia).

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(IC 1.6) A different notion of "information"

An informal discussion of the distinctions between our everyday usage of the word "information" and the information-theoretic notion of "information". A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F Attribution for image of TV static:

From playlist Information theory and Coding

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Fuzzy Logic Systems - Part 2: Fuzzy Inference System

This video is about Fuzzy Logic Systems - Part 2: Fuzzy Inference System

From playlist Fuzzy Logic

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O'Reilly Webcast: Information Security and Social Networks

Social networks are an information security game changer, and enterprises and their management are struggling to understand and deal with the security risks of social networks. Traditional information security protected your corporate IT perimeter. But that won't help in the web 2.0 era

From playlist O'Reilly Webcasts

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(IC 1.1) Information theory and Coding - Outline of topics

A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F Overview of central topics in Information theory and Coding. Compression (source coding) theory: Source coding theorem, Kraft-McMillan inequality, Rate-distortion theorem Error-correctio

From playlist Information theory and Coding

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Neural Network Architectures & Deep Learning

This video describes the variety of neural network architectures available to solve various problems in science ad engineering. Examples include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders. Book website: http://databookuw.com/ Steve Brunton

From playlist Data Science

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Fuzzy Logic Systems - Part 1: Introduction

This video is about Fuzzy Logic Systems - Part 1: Introduction

From playlist Fuzzy Logic

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Welcome - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

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Neural Network Overview

This lecture gives an overview of neural networks, which play an important role in machine learning today. Book website: http://databookuw.com/ Steve Brunton's website: eigensteve.com

From playlist Intro to Data Science

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22C3: Intrusion Detection Systems

Speakers: Matthias Petermann, Alien8 Elevated to the Next Level Currently there exist many different IDS techniques. However, none of them is the superior one. Best results can only be determined by a combination of them. We introduce an approach how to do that efficiently. For more inf

From playlist 22C3: Private Investigations

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Isabelle Bloch - Hybrid AI for Knowledge Representation and Model-based Image Understanding - (...)

This presentation will focus on hybrid AI, as a step towards explainability, more specifically in the domain of spatial reasoning and image understanding. Image understanding benefits from the modeling of knowledge about both the scene observed and the objects it contains as well as their

From playlist 8th edition of the Statistics & Computer Science Day for Data Science in Paris-Saclay, 9 March 2023

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the Internet (part 2)

An intro to the core protocols of the Internet, including IPv4, TCP, UDP, and HTTP. Part of a larger series teaching programming. See codeschool.org

From playlist The Internet

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CMU Neural Nets for NLP 2017 (17): Adversarial Learning

This lecture (by Graham Neubig) for CMU CS 11-747, Neural Networks for NLP (Fall 2017) covers: * (Generative) Adversarial Networks * Where to use the Adversary?: Features vs. Outputs * GANs on Discrete Outputs * Adversaries on Features Slides: http://phontron.com/class/nn4nlp2017/assets/

From playlist CMU Neural Nets for NLP 2017

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Evolutionary Approach to Clustering by Ujjwal Maulik

Program Summer Research Program on Dynamics of Complex Systems ORGANIZERS: Amit Apte, Soumitro Banerjee, Pranay Goel, Partha Guha, Neelima Gupte, Govindan Rangarajan and Somdatta Sinha DATE : 15 May 2019 to 12 July 2019 VENUE : Madhava hall for Summer School & Ramanujan hall f

From playlist Summer Research Program On Dynamics Of Complex Systems 2019

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ShmooCon 2013: astiff: Automated Static Analysis Framework

For more information and to download the video visit: http://bit.ly/shmoocon2013 Playlist ShmooCon 2013: http://bit.ly/Shmoo13 Speaker: Tyler Hudak Malware analysis consists of two phases -- static and dynamic analysis. Dynamic analysis, or analyzing the behavior of a sample, has already

From playlist ShmooCon 2013

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HAR 2009: Securing networks from an ISP perspective 4/6

Clip 4 Speaker: Bradley Freeman The role of the JANET CSIRT As an ISP attempting to secure a large network with 18 million users and 40Gbs link speeds is a challenging task, this talk will discuss how we attempt to make the JANET network a safer place for its users and the Interne

From playlist Hacking at Random (HAR) 2009

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7 2 Categories

Recorded: Spring 2014 Lecturer: Dr. Erin M. Buchanan Materials: created for Memory and Cognition (PSY 422) using Smith and Kosslyn (2006) Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdoom.com/page/other-courses/

From playlist PSY 422 Memory and Cognition with Dr. B

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22C3: A way to fuzzy democracy

Speakers: Svenja Schröder, Christiane Ruetten Using modern communication to transform the way we make political decisions As we can see by the German voting results in 2005, there is a huge disenchantment with politics in modern democracies. The voting people feel powerless in a governan

From playlist 22C3: Private Investigations

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Networking

If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.

From playlist Networking

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GNDCon 2.0 // Keynote, Harald Sack: „Die Welt ist klein und man trifft sich immer zweimal…“

Harald Sack (KIT / FIZ Karlsruhe) – Keynote Die Wissenschaften produzieren stetig wachsende Datenmengen. Deren effiziente Nutzung erfordert funktionierende Infrastrukturen. Ziel der Nationalen Forschungsdateninfrastruktur ist es, diese Datenbestände für das gesamte Wissenschaftssystem syst

From playlist ISE Conference Talks

Related pages

Tree (data structure) | Conditional mutual information | Statistical classification | Discretization of continuous features | Anomaly detection | Decision tree | Feature selection | Directed graph | Entropy (information theory) | Algorithm | Decision tree learning | Greedy algorithm | Statistical significance