The classification using 9 classes
Classes of Unique Face and Its Classification
... 1) Apply SVD on each of the face image for each class in the data base to get singular vector. 2) The obtained Singular Vector is applied with the fractional value of αand a optimized SVD values are obtained . 3) Each ...
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Feature Selection towards Soil Classification in the context of Fertility classes using Machine Learning
... International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-12, October 2019 Abstract: Soil is recognized as one of the most valuable entity which is responsible for ...
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Establishing Boundary Classes for the Quality Classification of Southeastern Black Sea Using Phytoplankton Biomass
... the classification of the ecological status of a water ...quality classification was determined in five different categories as “high, good, moderate, poor and ...the classification tool was ...
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Sparse Gaussian Process Classification With Multiple Classes
... of classification, individual patterns can carry a very different amount of “information” about the shape of the final predictor, however “information” is defined in this ...practice using simple greedy ...
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The theory of classification part 13: template classes and genericity
... expressed using the ...generic classes are well-behaved under inheritance, and can be extended at the same time as introducing, or instantiating the generic type ...
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Modelling Polysemy in Adjective Classes by Multi Label Classification
... We implemented an ensemble classifier by using the different levels of description as different subsets of features, and applying majority voting across the class proposals from each level. Intuitively, this ar- ...
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CLASSIFICATION OF SPARQL QUERIES INTO EQUIVALENCE CLASSES OF RELEVANT QUERIES
... queries using concepts and ideas inspired from the field of abstract ...By using only one query, specifically one arising from the covering query via an appropriate substitution, the evaluation of the ...
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Text Classification into Abstract Classes Based on Discourse Structure
... evaluation setting, using discourse improved the classification F-measure by 5.5 – 8.6% depend- ing on a classification sub-domain. There is a strong disattachment between mod- ern text learning ...
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Multiclass-Multilabel Classification with More Classes than Examples
... simpler classification algorithms, such as nearest neighbor ...web using Wikipedia categories, and assume that we have access to the log of an Internet search ...web using a nearest neighbor type ...
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Taking Advantage of the Web for Text Classification with Imbalanced Classes *
... text classification is that they commonly require high-quality training data to construct an accurate clas- ...text classification that combines under-sampling with a semi-supervised learning ...sults ...
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Classification with Multiple Classes using Naïve Bayes and Text Generation with a Small Data Set using a Recurrent Neural Network
... many classes, in addition to requiring many parameters to model demands an enormous amount of training data to adequately cover the possible contexts for the words ...
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Question Classification using Naive Bayes Classifier and Creating Missing Classes using Semantic Similarity in Question Answering System
... Semantic similarity is a measure of informativeness.It is computed based on the properties of the concepts and their relationships. Semantic similarity has been a part of computational linguistics and artificial ...
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Classification of economic data into multiple classes by means of evolutionary methods
... er using a dataset with diff erent sample amount for diff erent ...of using grammatical evolution is that we can easily analyse the program thanks to a human readable result and we can gain an insight of ...
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Classification of traffic flows into QoS classes by unsupervised learning and KNN clustering
... QoS classes? They could be decided either a priori or preferably without a priori assumptions using unsupervised clustering algorithms to discover the QoS classes naturally inherent in traffic ...
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Linear Discriminant Analysis for Two Classes via Removal of Classification Structure
... distribution. Using this data we obtained the discriminant plots (their direction vectors), then projected N t =3000 (extra) test observations on to the plots and computed the test error ...
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Inducing Fine Grained Semantic Classes via Hierarchical and Collective Classification
... semantic classes, which may not be adequate if seman- tic class information is intended to sup- port natural language ...semantic classes a noun phrase belongs ...lem using two techniques: ...
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A Cluster Based Classification of Imbalanced Data with Overlapping Regions Between Classes
... data classification problem with its main focus on improving the recognition of the minority class, while retaining high efficiency on classifying majority ...by using Euclidean distance ...clustered ...
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Handling Imbalanced Classes: Feature Based Variance Ranking Techniques for Classification
... by using only 5 selected features instead of a total of 10 features in a data mining process, considering the time and other resources it may take to acquire all 10 that may not be necessary to the predic- ...like ...
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Structure-Based Classification Defines the Discrete Conformational Classes Adopted by the Arenaviral GP1
... Human embryonic kidney (HEK) 293T cells (ATCC CRL-1573) were transiently transfected with the desired protein constructs in the presence of the class 1 ␣-mannosidase inhibitor kifunensine (53). Cell supernatants were ...
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Are the ASISA Standards with Respect to Unit Trust Classification Representative of Homogeneous Risk Classes?
... and it is used to compare with the group LSD to test the null hypothesis: the systematic risk of the unit trust is the same as that of the group mean vs. the alternative hypothesis that the systematic risk is different. ...
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