subset selection
Using Document Summarization Techniques for Speech Data Subset Selection
... priori selection of a data set before (re-)training a system; in this case the goal is to subselect the existing data set as well as possible, eliminating redundant infor- mation; (b) selection for ...
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Optimal Features Subset Selection and Classification for Iris Recognition
... In this paper, a new iris recognition method is proposed using an efficient iris segmentation approach based on the collarette area localization with the incorporation of the eyelashes and the eyelids detection techniques. ...
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Evaluation of Feature Subset Selection, Feature Weighting, and Prototype Selection for Biomedical Applications
... feature subset and feature weighting tasks both dis- play slight improvements or retention of the performance for all values of ...feature subset selection and feature weighting techniques used in ...
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Approximate Submodularity and its Applications: Subset Selection, Sparse Approximation and Dictionary Selection
... our subset selection formulation, since the goal in sparse recovery is to recover the true coefficients of the sparse signal, as opposed to our problem of minimizing the prediction error of an arbitrary ...
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A Novel Feature Subset Selection Algorithm for Software Defect Prediction
... Two level feature subset selection algorithms effectively deal with redundant and irrelevant attributes. The first level of algorithm removes the redundant attributes and irrelevant attributes are ...
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Survey on Feature Subset Selection Algorithm in Brain Interaction Patterns
... Feature selection for interaction based clustering in interaction patterns among brain images by using feature subset selection ...Feature selection for interaction based clustering in ...
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Ensemble feature subset selection technique in spam detection system
... feature subset selection and ensemble classification are necessary to address these ...feature selection techniques for spam detection, based on three feature selection algorithms: Novel ...
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New feature subset selection procedures for classification of expression profiles
... For testing our methods we used two public datasets, one representing colon (tumor/normal) tissues [10], and the other representing acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) [9] (see also ...
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A FAST CLUSTERING-BASED FEATURE SUBSET SELECTION ALGORITHM
... Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of ...feature selection algorithm is basically evaluated from ...
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A Review Of Fast Clustering-Based Feature Subset Selection Algorithm
... feature selection algorithm may be seen as the combination of a search technique and with an evaluation measure which scores the different feature ...possible subset of features finding and minimizes the ...
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Pareto Optimization for Subset Selection with Dynamic Cost Constraints
... In this paper, we consider the subset selection problem for function f with constraint bound B which changes over time. We point out that adaptive variants of greedy approaches commonly used in the area of ...
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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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A FAST Algorithm for High Dimensional Data using Clustering Based Feature Subset Selection
... a subset of good features with respect to the target concepts, feature subset selection is an effective way for reducing dimensionality, removing irrelevant data, increasing learning accuracy, and ...
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Title: A Framework for Mining High Dimensional Data for Feature Subset Selection
... feature subset selection for high dimensional ...as subset of ...feature subset so as to be very useful for many applications in the ...
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Feature Subset Selection in Conditional Random Fields for Named Entity Recognition
... In the application of Conditional Random Fields (CRF), a huge number of features is typically taken into ac- count. These models can deal with inter-dependent and correlated data with an enormous complexity. The ...
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Maximum Volume Subset Selection for Anchored Boxes
... Let B be a set of n axis-parallel boxes in R d such that each box has a corner at the origin and the other corner in the positive quadrant of R d , and let k be a positive integer. We study the problem of selecting k ...
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Feature Subset Selection Using Genetic Algorithm for Named Entity Recognition
... Feature selection, also known as variable selection, feature reduction, attribute selection or variable subset selection, is the technique, commonly used in machine learning, of ...
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AdaBoost Ensemble Learning Technique for Optimal Feature Subset Selection
... is subset generation which contains three stages that are implementing learning classifier algorithms, applying best first search technique and selecting the highest three ...feature selection search by ...
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CLUSTERING-BASED FEATURE SUBSET SELECTION ALGORITHM USING FAST
... feature selection as a part of the training process and are usually specific to given learning algorithms, and therefore may be more efficient than the other three ...
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Feature Subset Selection for High Dimensional Data using Clustering Techniques
... from different perspective and summarizing it into useful information (Information that can be used to increase revenue, cuts costs or both). Database contains large volume of attributes or dimensions which are further ...
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