The model performance using a two-feature set
Signature Verification Using Envelope and Histogram Feature Set
... on two sets of features extracted from the signature image. First set of feature consists of envelope features which are obtained by scanning the signature from all the four sides and recording their ...
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Rough Set Feature Selection Using Bat Algorithm
... Association is one of the best known data mining technique. In association, a pattern is discovered based on a relationship between items in the same transaction. That’s is the reason why association technique is also ...
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Rough Set Feature Selection Using Bat Algorithm
... Classification is a classic data mining technique based on machine learning. Basically classification is used to classify each item in a set of data into one of predefined set of classes or groups. ...
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A two-stage hybrid model by using artificial neural networks as feature construction algorithms
... a two-stage hybrid approach with neural networks as the new feature construction algorithms for bankcard response ...hybrid model uses a very simpleneural network structure as the new feature ...
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Survey on Rough Set Feature Selection Using Evolutionary Algorithm
... rough set was originally proposed as a mathematical approach to handle imprecision, vagueness, and uncertainty in data ...by two definable or observable subsets called lower and upper ...By using the ...
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Fabric Image Retrieval Using Combined Feature Set and SVM
... III. P ROPOSED A PPROACH This chapter aims at presenting the overview of the proposed methodology. The proposed work focuses on texture rich features, which is available on fabric images. The textile industry lacks CBIR ...
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Ranking Model with a Reduced Feature Set for an Automated Question Generation System
... The sentiments of the raters were shared, which gave us an idea about what is not appealing to them. We formalized this feedback using the grammatical framework of English sentence struc- ture. This exercise led ...
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Feature Aided Switching Model Set Approach for Maneuvering Target Tracking
... the model probability histories of the three MM ...CV model matching with target motion mode is employed in VSMM ...designed model-set constituted of three models is employed in AMM and IMM ...
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Comparison of Feature Selection Methods for Chronic Kidney Data Set using Data Mining Classification Analytical Model
... diseases using the statistical medical data with the help of different machine learning ...without using the complex clinical ...a feature model construction and comparative analysis for ...
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Comparison of feature selection method for chronic kidney data set using data mining classification analytical model
... diseases using the statistical medical data with the help of different m achine learning ...without using the complex clinical ...a feature model construction and comparative analysis for ...
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Two-feature voiced/unvoiced classifier using wavelets
... its performance evaluated. The algorithm is based on extracting two features of the input speech: the ra- tio of the average energy in the wavelet low-subbands to that in the wavelet highest-subband, and ...
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SeeDev Binary Event Extraction using SVMs and a Rich Feature Set
... 4.2 Error analysis In Table 4.2 we show the confusion matrix for 16 classifiers of our system, when evaluated over the development dataset. The remaining 6 classifiers were left out as they have 0 predictions and are ...
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Sentiment Classification using Rough Set based Hybrid Feature Selection
... in two steps. Firstly, Information Gain (IG) of each feature is comput- ed and all the features are taken which has infor- mation gain value to be greater than ...the feature vector, by this a lot ...
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Enrichment of security using feature Set and order sequence graphical authentication
... Image based authentication allows user to create graphical password which has advantages over text-based passwords. Graphical passwords have been designed to make passwords more memorable and easier for people to use. In ...
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Semantic Clustering of Genomic Documents using GO Terms as Feature Set
... Documents Using Go Terms as Feature Set ...the set of keywords which can be represented as features for grouping the documents ...found using structural path between the ...documents ...
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A Preliminary Performance Comparison of Two Feature Sets for Encrypted Traffic Classification
... the performance of two feature sets using ...algorithms using packet header and flow based ...that feature set based on packet header is compatible with the statistical ...
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A Machine Learning Approach to Automatic Term Extraction using a Rich Feature Set
... As the fourth contribution, we minimized the problem of high dimensionality (as mentioned, the second ATE problem) by means of the use of two different cut-offs (C1 and C2). By reducing the number of TCs, fewer ...
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LT3: Sentiment Classification in User Generated Content Using a Rich Feature Set
... test set, obtaining an F-score of 86.28, while the best performance for this data genre is an F-score of ...in performance on the Twitter2014 Sarcasm test ...
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Student Performance Prediction Model Based on Discriminative Feature Selection
... researchers. Feature selection method is a necessary link in data mining and machine learning, it is widely used in the classification analysis of text data, image and video data and bio- omics data, and plays an ...
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Performance improvement in VSLAM using stabilized feature points
... in feature extraction (FE) and dead reckoning (DR) blocks, ...robot model are used and the sensor measurement model is utilized to predict the ...
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