A hybrid PSO/ACO algorithm for classification

Holden, Nicholas; Freitas, Alex A.

doi:10.1145/1274000.1274080

Cited by 43 publications

(25 citation statements)

References 7 publications

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“…For example, by combining the strengths of AntMiner and particle swarm optimization [27], a resultant hybrid algorithm provides a very promising performance thanks to their specific capabilities in handling continuous attribute and nominal attributevalue construction. Ant-Tree-Miner [28] induces decision tress rather than a set of rules, which is consequently quite different from AntMiner and its variants.…”

Section: Aco For Flat Single Label Classificationmentioning

confidence: 99%

Orderly Roulette Selection Based Ant Colony Algorithm for Hierarchical Multilabel Protein Function Prediction

Liang¹,

Guo²,

Sun³

et al. 2017

Mathematical Problems in Engineering

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Ant colony optimization (ACO) algorithms have been successfully applied to identify classification rules in data mining. This paper proposes a new ant colony optimization algorithm, named ℎ AntMiner order , for the hierarchical multilabel classification problem in protein function prediction. The proposed algorithm is characterized by an orderly roulette selection strategy that distinguishes the merits of the data attributes through attributes importance ranking in classification model construction. A new pheromone update strategy is introduced to prevent the algorithm from getting trapped in local optima and thus leading to more efficient identification of classification rules. The comparison studies to other closely related algorithms on 16 publicly available datasets reveal the efficiency of the proposed algorithm.

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Section: Aco For Flat Single Label Classificationmentioning

confidence: 99%

Orderly Roulette Selection Based Ant Colony Algorithm for Hierarchical Multilabel Protein Function Prediction

Liang¹,

Guo²,

Sun³

et al. 2017

Mathematical Problems in Engineering

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“…Posts are processed in order to: i) Identify and extract users' opinions and ii) automatically weight the users' comments according to the presence or not of arguments justifying their opinion about a certain service, product or governmental decision using the PSO/ACO2 [18,57] algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, instead of the "traditional" artificial intelligence techniques (e.g neural networks, support vector machine, decision trees, etc) one of the latest biologically inspired intelligent methods namely the hybrid PSO/ACO2 algorithm [18] is used. Furthermore, the classification results of the C4.5 algorithm (decision trees) are provided for comparison purposes.…”

Section: Introductionmentioning

confidence: 99%

Using Bio-inspired intelligence for Web opinion Mining

Stylios¹,

Katsis²,

Christodoulakis³

2014

IJCA

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This work proposes a bio-inspired based methodology in order to extract and evaluate user's web texts / posts. To validate the methodology, a dataset is constructed using real data arising from Greek fora. The obtained results are compared with a commonly used machine learning technique (decision trees-C4.5 algorithm). The bio-inspired algorithm (namely the hybrid PSO/ACO2 algorithm) achieved average classification accuracy 90.59% in a 10 fold cross validation experiment, outperforming the C4.5 algorithm (83.66%). The proposed methodology could be easily integrated with a decision support system providing services in the fields of ecommerce or e-government in order to help merchants acquire customer satisfaction or public administrators capture common understanding.

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“…Other works on Ant-Miner involve (Smaldon J. et al 2006) [15] in which an algorithm is designed for unordered rule sets has been presented. PSO (Holden N. et al 2007) [16] algorithm is used for unending valued attributes and ACO for formally valued features and these two algorithms are jointly used to build rules. [17,18].…”

Section: Introductionmentioning

confidence: 99%

WACO for Mammogram Classification

Kumari¹,

Sowrya²

2016

IJCA

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Breast cancer is one of the ruinous diseases causing more number of deaths in women. Many efforts are being made to develop efficient techniques to identify the breast cancer at early stage. This paper implements weaver ant colony optimization (WACO) for classifying mammograms. The behavior of weaver ants' to bind the neurons between the layer to make the path to find the output of Neural Network(NN). The unique nest building behavior of Weaver ants' made a considerable remark, NN have proved to be one of the best methods for classification & WACO is used for optimized pathfinding. Each layer of NN is considered as one leaf and the leaves are divided into as many portions equal to the number of neurons,& let ants connect portion of leaf from one layer to another, makes the weight connection in the NN. The task is accomplished by using a NN with a back propagation technique (BPT). To determine the usefulness of WACO based Neural Network (NN)closed nests building behavior made us change the architecture of BPN. Weaver ants show indirect message between ants to find the shortest path between their nest and food sources. These ants ability is to construct nests by weaving together leaves using larval silk .Local Binary Pattern is a method which can be used extract the features for identifying the breast cancer abnormality by mammogram. Multilayer perceptron (MLP) and support vector machine for mammogram classification and mammogram images are preprocessed to reduce noise and detect the background of the mammogram to extract the required features. This paper implements WACO for classifying mammograms. Here we used MIAS database which describes the mammogram is in which stage benign or normal stage

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A hybrid PSO/ACO algorithm for classification

Cited by 43 publications

References 7 publications

Orderly Roulette Selection Based Ant Colony Algorithm for Hierarchical Multilabel Protein Function Prediction

Orderly Roulette Selection Based Ant Colony Algorithm for Hierarchical Multilabel Protein Function Prediction

Using Bio-inspired intelligence for Web opinion Mining

WACO for Mammogram Classification

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