Feature Subset Selection Results
Feature Subset Selection in Spam Detection
... The results of this paper show the performance near to 100% and ...in feature selection and the ability of MLP classifier for generating high accuracy and decrease the time of ...
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Evaluation of Feature Subset Selection, Feature Weighting, and Prototype Selection for Biomedical Applications
... the results from the three datasets summarised in this section demonstrate that measuring performance by using the overall accuracy of a classifier is inaccurate and insufficient when there is an unequal ...
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Gait Feature Subset Selection by Mutual Information
... Gait Feature Subset Selection by Mutual Information Baofeng Guo and ...Abstract— Feature selection is an important pre-processing step for pattern ...while, feature ...
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Feature Subset Selection Using a Genetic Algorithm
... The results presented in this paper are based experiments using neural networks constructed by DistAl ...maximal subset of training patterns belonging to a single ...process results in an empty ...
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Feature subset selection problem on microarray data
... possible subset is required in order to obtain the optimal feature ...best feature subsets and perform induction with artificial neural ...better results when compared to sequential backward ...
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Ensembles of Instance Selection Methods based on Feature Subset
... instance selection were developed and an overview of them can be found in 2,3,4 ...instance selection as automatic data filters and running different machine learning methods on the top of the selected ...
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Ensemble feature subset selection technique in spam detection system
... attributes, feature subset selection and ensemble classification are necessary to address these ...ensemble feature selection techniques for spam detection, based on three ...
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Survey on Feature Subset Selection Algorithm in Brain Interaction Patterns
... II. RELATED WORK In this paper [1] IKM achieves good results on synthetic data and on real world data. It is scalable and robust against noise. Ranking Algorithm improves the efficiency of clustering result there ...
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New feature subset selection procedures for classification of expression profiles
... Conclusions We propose a new method for evaluating combinations of genes. Comparing the top-ranked genes ranked by gene-pair evaluation to the gene sets selected by two standard methods, we demonstrate that the gene sets ...
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Efficient Feature Subset Selection Algorithm for High Dimensional Data
... proposes feature selection algorithm termed as IFSA (Information gain based Feature subset Selection Algorithm) to remove irrelevant, noisy and redundant features and produce small ...
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A Review Of Fast Clustering-Based Feature Subset Selection Algorithm
... crossover, selection and inheritance to select a feature ...often results in better classification accuracy of the selected subsets than the accuracy achieved with filter methods ([25, 26, ...model ...
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A BINARY PSO-ACO HYBRID ALGORITHM FOR FEATURE SUBSET SELECTION
... ABSTRACT Feature Selection is the process of selecting a subset of features available, allowing a certain objective function to be optimized, from the data containing noisy,irrelevant and redundant ...
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CLUSTERING-BASED FEATURE SUBSET SELECTION ALGORITHM USING FAST
... ABSTRACT Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of ...A feature selection ...
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IMPLEMENTATION OF CLUSTERING-BASED FEATURE SUBSET SELECTION ALGORITHM-FAST
... Feature selection involves recognizing a subset of maximum of helpful features that produces attuned results as the unique set of ...filter subset selection algorithm for ...
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Addressing low dimensionality feature subset selection: reliefF(-k) or extended correlation-based feature selection(eCFS)?
... data selection at the feature level, some options proposed in a prior work as well as an advanced contemporary approach have been ...of feature selection according to the solution type and the ...
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Mixed variable ant colony optimization technique for feature subset selection and model selection
... suitable feature subset and optimizing SVM parameters must occur simultaneously, because these processes affect each other which in turn will affect the SVM ...algorithm. Results showed that the ...
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A Minimal Subset of Features Using Feature Selection for Handwritten Digit Recognition
... the results obtained in the previous section can be optimized using different ...these results since our tar- get was to find the most suitable classification techniques that can be used to solve the ...
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques
... Liu and their colleagues described a hierarchical ID model based on the PCANN, which has been used for adaptive computing for both misuse detection and anomaly detection (Liu et al. 2007). The design of PCANN based ...
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Feature Subset Selection Using Genetic Algorithm for Named Entity Recognition
... The main approaches to NER can be grouped into three main categories, namely rule-based, machine learning based and hybrid approach. Rule based approaches focus on extracting names using a number of handcrafted rules ...
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Feature Subset Selection in Conditional Random Fields for Named Entity Recognition
... The methods have been evaluated on two domains, showing a decrease of computing time and complexity of the model. The F 1 measure varies slightly. Summarizing, IG OAA is the best filter approach, a lower number of ...
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