Search Results - (( data selection method algorithm ) OR ( data generation method algorithm ))
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…All the techniques assist the decision tree to find the most optimal attributes in each generation of the tree. Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…This method consists of 2 phases which are the random data generation and then update of the probabilities based on the performance of the data generated. …”
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5
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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Enhance efficiency of answering XML keyword query using incompact structure of MCCTree
Published 2012“…If the result cannot be used directly by the ranking method, the algorithm has an ineffective process. …”
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7
A new ant based rule extraction algorithm for web classification
Published 2011“…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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Monograph -
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A clonal selection algorithm model for daily rainfall data prediction
Published 2014“…This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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Comparison of attribute selection methods for web texts categorization
Published 2010“…This paper presents a study on the performance of attribute selection methods to be used with Ant-Miner algorithm for web text categorization.The new generated data set by each attribute selection method was classified with Ant-Miner to see the performance in terms of predictive accuracy and the number of rules generated.The results of classification were also compared to C4.5 algorithm.…”
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Conference or Workshop Item -
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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
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Book Section -
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The new efficient and accurate attribute-oriented clustering algorithms for categorical data
Published 2012“…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
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15
Mutable composite firefly algorithm for gene selection in microarray based cancer classification
Published 2022“…This result indicates that the proposed algorithm is one of the competitive alternatives in feature selection, which later contributes to the analysis of microarray data.…”
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16
Discovering optimal clusters using firefly algorithm
Published 2016“…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii
Published 2012“…Clonal selection algorithm (CLONALG) in AIS is one of the proposed methods to be obtained in real UPSR. …”
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Thesis -
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Multiple and solid data background scheme for testing static single cell faults on SRAM memories
Published 2013“…Therefore, the purpose of this thesis is to introduce a Data Background (DB) scheme to generate an optimal March Test Algorithm (MTA) for detecting faults of memory that are undetectable using existing algorithms. …”
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