[PDF] Top 20 Information Gain Feature Selection for Multi-Label Classification
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Information Gain Feature Selection for Multi-Label Classification
... single label from a set of class labels. More specifically, the single- label classification problem can be stated as the process of predicting the class label of new instances described by their ... See full document
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Information Gain as a Feature Selection Method for the Efficient Classification of Influenza Based on Viral Hosts
... subtype classification accuracy of 100%. Accuracies of host classification ranged from 50% to 100%, depending on ...host classification accuracies, the classification performance was reduced ... See full document
7
Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.
... extract information from high- resolution remote sensing images because of its rich geometry and the texture ...to information extraction conducted on the same data using different ...object-oriented ... See full document
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MULTI-LABEL CLASSIFICATION OF PRODUCT REVIEWS USING STRUCTURED SVM
... popular feature extraction method which reflects the relevance of a word in a particular document among the ...in Information Retrieval and Text Mining and its value is directly proportional to the number ... See full document
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Document features selection using background knowledge and word clustering technique
... of feature space is very high, which increases the cost and reduces the performance of classification algorithms (Sebastiani, 2002; Shang et ...Therefore, classification algorithms need some methods ... See full document
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Giovani da Costa Caetano3 Carla Daniela Suguimoto Leite3 Cristina Moreira Bonafé4 Mariele Freitas Sousa3 Robledo de Almeida Torres3
... Data from two strains of meat quail (Coturnix coturnix) from Poultry Breeding Program at Department of Animal Sciences of the Universidade Federal de Viçosa, Brazil were used in this study. Animals were originally ... See full document
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A Parallel Computing Hybrid Approach for Feature Selection
... Este trabalho explora duas maneiras de paralelizar o algoritmo proposto. A primeira demonstra como ´ e poss´ıvel fazˆ e-lo utilizando maquinas em locais diferentes. Por isso utilizada o paradigma de mem´ oria ... See full document
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Towards an accurate sleep apnea detection based on ECG signal: The quintessential of a wise feature selection
... the Feature Extraction is focused not only on the Heart Rate Variability (HRV), but also in the ECG-Derived Respiration ...the feature selec- tion and the classification are inter-leaved aiming at to ... See full document
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Economical Structure for Multi-feature Music Indexing
... music feature strings [2][3][9][12][13][18][20] or numeric values [16][17] such that the indices can be created for music ...introduced multi-feature index structures for music retrievals while most ... See full document
5
Feature Selection via Chaotic Antlion Optimization.
... the information is ...problem. Feature selection (attribute reduction) is a tech- nique for solving classification and regression problems, and it is employed to identify a subset of the ... See full document
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A new method for feature selection based on fuzzy similarity measures using multi objective genetic algorithm
... a feature selection method based on fuzzy similarity measures by multi objective genetic algorithm (FSFSM – MOGA) is ...the multi – objective genetic ...on feature selection ... See full document
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Prediction of nucleosome positioning based on transcription factor binding sites.
... A number of studies have been performed in an attempt to determine nucleosome positioning signals at the level of TFs or transcription factor binding sites (TFBSs), which are bound by TFs to enable gene expression ... See full document
7
Improving Activity Recognition Accuracy in Ambient-Assisted Living Systems by Automated Feature Engineering
... generic feature engineering method for selecting robust features from a variety of sensors, which can be used for generating reliable classification ...two-phase feature selection, the number ... See full document
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Selection and genetic gain in rubber tree (Hevea) populations using a mixed mating system
... Combined selection tends to select many individuals from certain families because of the greater weight given to the progeny ...be selection against inbred individuals with undesirable traits, as long as ... See full document
10
PERFORMANCE EVALUATION OF CONTENT BASED IMAGE RETRIEVAL FOR MEDICAL IMAGES
... generating feature vectors in content based image retrieval (CBIR) systems. Feature vectors are stored in feature databases and images ...visual information in medical ...a ... See full document
7
Bayesian Multi-Trait Analysis Reveals a Useful Tool to Increase Oil Concentration and to Decrease Toxicity in Jatropha curcas L.
... Geweke convergence criterion indicates convergence for all dispersion parameters when gener- ating 100,000 MCMC chains, 40,000 samples for burn-in and a sampling interval of 10, totaling 6,000 effective samples used for ... See full document
14
Selecting Features of Single Lead ECG Signal for Automatic Sleep Stages Classification using Correlation-based Feature Subset Selection
... a multi-stage Support Vector Machines (SVM) ...three-stage multi-class SVMs are needed and perform good result with high ...112 feature measures can be extracted; 60 for RR time series and 52 for EDR ... See full document
10
Summing up the Information - A Classification
... to information and diagnosis may be considered as an option for developing ...provide information about its potential impact in reducing the morbidity associated with MPS ... See full document
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GENETIC GAIN FROM DIFFERENT SELECTION METHODS IN Eucalyptus
... genetic gain for different selection ...The selection of the progenies for establishing a Clonal Seed Orchard was based on the analysis by location, joint analysis and on the harmonic mean of the ... See full document
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A Novel Texture Classification Procedure by using Association Rules
... Texture classification aims to assign texture labels to unknown textures, according to training samples and classification ...statistical information, and automatically identify the structures that ... See full document
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