feature based data sets
An Exponential Kernel based Fuzzy Rough Sets Model for Feature Selection
... all data sets are deleted and all the algorithms produce distinct subset of ...any data set in the ...different feature subsets to produce the best classification ...kernel based fuzzy ...
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MRMR BA: A HYBRID GENE SELECTION ALGORITHM FOR CANCER CLASSIFICATION
... taxonomy based features to address data sets from various fields, these taxonomy feature types can also be used to address ambiguous questions resulted from the existence of shared or ...
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Extracting Complex Biological Events with Rich Graph Based Feature Sets
... implementations currently available. Analogously to the binary SVMs, multi-class SVMs have a reg- ularization parameter that determines the trade-off between the training error and the complexity of the learned concept. ...
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Web of Service Software Reusability Prediction using Heterogenous Ensemble Classifier
... exploiting data from different sources and combined the base learners by means of a weighted voting ...or data seems ...source data having imagery of multiple spectral, Synthetic Aperture Radar (SAR) ...
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Feature Correlation Measure Based Real Time Discrimination Prevention with Transactional Data Sets using Social Networks
... transactional data have been identified, but does not produced expected performance ...a feature correlation measure based approach has been presented in this ...transactional data set and ...
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Distances between Data Sets Based on Summary Statistics
... world data sets and several feature sets. We had 7 data sets: Bible, a collection of 73 books from the Bible, 1 Addresses, a collection of 55 inaugu- ral addresses given by the ...
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Combination of Feature Selection and Learning Methods for IoT Data Fusion
... five data fusion schemes for the Internet of Things (IoT) scenario, which are Relief and Perceptron (Re-P), Relief and Genetic Algorithm Particle Swarm Optimization (Re- GAPSO), Genetic Algorithm and Artificial ...
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Automatic Discovery of Feature Sets for Dependency Parsing
... Transition- based methods share common properties and build a dependency graph from a sequence of ac- tions, where each action is determined using a fea- ture ...a data-driven context, the func- tion is ...
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Learning Condensed Feature Representations from Large Unsupervised Data Sets for Supervised Learning
... unsupervised data to supplement supervised ...‘clustering- based word representations (CWR)’ induced from unsupervised data as additional features of super- vised learning has demonstrated ...
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Feature Subset Selection using Rough Sets for High Dimensional Data
... The proposed approach removes irrelevant and redundant features using filter and clustering-based method. A cluster consists of features. Each cluster is treated as a single feature and thus dimensionality ...
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Feature Selection for Small Sample Sets with High Dimensional Data Using Heuristic Hybrid Approach
... The proposed method is considered as an embedded method since it makes use of some filter-based methods together with genetic algorithm (GA). In this paper, a novel hybrid feature selection approach is ...
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A Decision Tree of Bigrams is an Accurate Predictor of Word Sense
... Two feature sets are selected from the training data based on the top 100 ranked bigrams according to the power divergence statistic and the Dice CoeÆcient.. The bigram must have oc- cur[r] ...
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Complementary feature sets for optimal face recognition
... complementary feature sets is proposed, where the global information of the face images is extracted by the ZM descriptor employ- ing its rotation invariance characteristic, while the LBP/ LTP descriptor ...
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Design Pattern Identification and Its Models
... are based on statistics and ...of feature sets. These Feature Sets are chosen in such a way that different patterns occupy non- overlapping feature ...the feature set is ...
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DATA MINING ANALYSIS TO DRAW UP DATA SETS BASED ON AGGREGATIONS
... In above written query we can see that the is query clearly makes us understand the intension behind it means to say that the user here is trying to group the names from the register table. Grouping here is done only ...
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DATA MINING ANALYSIS TO DRAW UP DATA SETS BASED ON AGGREGATIONS
... relevant data from the very complex ...the data in an efficient ...input data from more than one table and display results as required by the third party to have a simplified look and moreover gives ...
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Hierarchical relaxed partitioning system for activity recognition
... 5D feature descriptor with a hidden Markov model (HMM) to detect the fence climbing ...a feature vector, for activity ...curve based methods are sensitive to the silhouette contour, occlusion, ...
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DACS Dewey index based Arabic Document Categorization System
... applied K-nearest neighborhood algorithm, and extract keywords based on the document frequency TFIDF method with a micro-average precision 0.95.Noaman et al. [12] extracted roots as features for the classifier, ...
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Diversity and the Film Industry: An Analysis of the 2014 UIS Survey on Feature Film Statistics
... on data available in the UIS Data Centre ...of feature films can be analysed by the presence of different linguistic categories, ...i.e. feature films using one language (monolingual) or a ...
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Using Gazetteers in Discriminative Information Extraction
... In work developed independently and in parallel to the work presented here, Sutton et al. (2006) iden- tify general problems with gazetteer features and propose a solution similar to ours. They present re- sults on ...
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