ai4r.org

AI4R :: Artificial Intelligence for Ruby

AI4R : Artificial Intelligence for Ruby. AI4R is a collection of ruby algorithm implementations, covering several Artificial intelligence fields, and simple practical examples using them. A Ruby playground for AI researchers. It implements:. Multilayer perceptron with Backpropagation learning. Automatic classifiers (Machine Learning). PRISM (J. Cendrowska, 1987). OneR (AKA One Attribute Rule, 1R). IB1 (D. Aha, D. Kibler - 1991). Optimization of the Travelling salesman problem (NP-hard problem).

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AI4R :: Artificial Intelligence for Ruby | ai4r.org Reviews

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AI4R : Artificial Intelligence for Ruby. AI4R is a collection of ruby algorithm implementations, covering several Artificial intelligence fields, and simple practical examples using them. A Ruby playground for AI researchers. It implements:. Multilayer perceptron with Backpropagation learning. Automatic classifiers (Machine Learning). PRISM (J. Cendrowska, 1987). OneR (AKA One Attribute Rule, 1R). IB1 (D. Aha, D. Kibler - 1991). Optimization of the Travelling salesman problem (NP-hard problem).

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1 index

2 practical examples

3 genetic algorithms

4 machine learning

5 neural networks

6 downloads

7 source code repository

8 api doc rdoc

9 introduction

10 how to install

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AI4R :: Artificial Intelligence for Ruby | ai4r.org Reviews

https://ai4r.org

AI4R : Artificial Intelligence for Ruby. AI4R is a collection of ruby algorithm implementations, covering several Artificial intelligence fields, and simple practical examples using them. A Ruby playground for AI researchers. It implements:. Multilayer perceptron with Backpropagation learning. Automatic classifiers (Machine Learning). PRISM (J. Cendrowska, 1987). OneR (AKA One Attribute Rule, 1R). IB1 (D. Aha, D. Kibler - 1991). Optimization of the Travelling salesman problem (NP-hard problem).

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ai4r.org

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class Ai4r::Clusterers::CentroidLinkage - ar4r - Artificial Intelligence For Ruby - API DOC

http://www.ai4r.org/rdoc/Ai4r/Clusterers/CentroidLinkage.html

Class Ai4r: Clusterers: CentroidLinkage. Implementation of an Agglomerative Hierarchical clusterer with centroid linkage algorithm, aka unweighted pair group method centroid (UPGMC) (Everitt et al., 2001 ; Jain and Dubes, 1988 ; Sokal and Michener, 1958 ) Hierarchical clusterer create one cluster per element, and then progressively merge clusters, until the required number of clusters is reached. The distance between clusters is the squared euclidean distance between their centroids. Cx, ci, cj).

2

class Ai4r::NeuralNetwork::Backpropagation - ar4r - Artificial Intelligence For Ruby - API DOC

http://www.ai4r.org/rdoc/Ai4r/NeuralNetwork/Backpropagation.html

How to use it. Class Ai4r: NeuralNetwork: Backpropagation. This is an implementation of a multilayer perceptron network, using the backpropagation algorithm for learning. Is a supervised learning technique (described by Paul Werbos in 1974, and further developed by David E. Rumelhart, Geoffrey E. Hinton and Ronald J. Williams in 1986). Support for any network architecture (number of layers and neurons). Optional usage of bias. Configurable initial weight function. 100% ruby code, no external dependency.

3

class Ai4r::Clusterers::CompleteLinkage - ar4r - Artificial Intelligence For Ruby - API DOC

http://www.ai4r.org/rdoc/Ai4r/Clusterers/CompleteLinkage.html

Distance between item and cluster. Class Ai4r: Clusterers: CompleteLinkage. Implementation of a Hierarchical clusterer with complete linkage (Everitt et al., 2001 ; Jain and Dubes, 1988 ; Sorensen, 1948 ). Hierarchical clusterer create one cluster per element, and then progressively merge clusters, until the required number of clusters is reached. With complete linkage, the distance between two clusters is computed as the maximum distance between elements of each cluster. Data set, number of clusters).

4

class Ai4r::Clusterers::AverageLinkage - ar4r - Artificial Intelligence For Ruby - API DOC

http://www.ai4r.org/rdoc/Ai4r/Clusterers/AverageLinkage.html

Class Ai4r: Clusterers: AverageLinkage. D(cx, (ci U cj) = (D(cx, ci) D(cx, cj) / 2. Data set, number of clusters). Click to toggle source. Build a new clusterer, using data examples found in data set. Items will be clustered in number of clusters different clusters. File lib/ai4r/clusterers/average linkage.rb, line 38. Click to toggle source. This algorithms does not allow classification of new data items once it has been built. Rebuild the cluster including you data element. Cx, ci, cj).

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ar4r - Artificial Intelligence For Ruby - API DOC

http://www.ai4r.org/rdoc/index.html

Class and Module Index. Ai4r: Classifiers: NaiveBayes: DataEntry. Ai4r: Data: Parameterizable: ClassMethods. This project aims to produce ruby implementations of algorithms covering several Artificial intelligence fields. Where can I find the lastest code and info on this project? How to install ¶. Include require statements in your code:. More Info ¶. AI4R Project site: www.ai4r.org. RDoc site: www.ai4r.org/rdoc/index.html. Email address: (sergio (at) gmail (dot) com).

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Self-organizing map - Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Self-organizing_map

From Wikipedia, the free encyclopedia. This article may require cleanup. To meet Wikipedia's quality standards. Has been specified. Please help improve this article. Learn how and when to remove this template message. Relevance vector machine (RVM). Support vector machine (SVM). Or self-organising feature map. Is a type of artificial neural network. ANN) that is trained using unsupervised learning. Self-organizing maps are different from other artificial neural networks as they apply competitive learning.

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AI4R :: Artificial Intelligence for Ruby

AI4R : Artificial Intelligence for Ruby. AI4R is a collection of ruby algorithm implementations, covering several Artificial intelligence fields, and simple practical examples using them. A Ruby playground for AI researchers. It implements:. Multilayer perceptron with Backpropagation learning. Automatic classifiers (Machine Learning). PRISM (J. Cendrowska, 1987). OneR (AKA One Attribute Rule, 1R). IB1 (D. Aha, D. Kibler - 1991). Optimization of the Travelling salesman problem (NP-hard problem).

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