Classification accuracy
The Positional Effect in Soft Classification Accuracy Assessment
... soft classification algorithms and soft classification accuracy assessment beyond the traditional hard ...hard classification accuracy assessment are appropriate for the soft ...the ...
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Evaluation of Text Classification Accuracy
... In this project we wanted to test how the use of stemming, a transformation method, effects classification accuracy. We also wanted to have both the stemmed and non-stemmed data available and be able to use ...
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Analysis of feature training set for improving classification accuracy
... the classification accuracy is majority ...8 classification results contained in 256 ms with a window increment of 32 ms and makes decision based on the frequency of class ...
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Maximizing Classification Accuracy in Native Language Identification
... Our original interest in NLI began with a curios- ity about the evidence it can provide for the pres- ence of crosslinguistic influence in nonnative speakers’ speech and writing. We believe that NLI strongly supports ...
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Methods of digital classification accuracy assessment
... List Figure 5-1 GML Classification Figure 5-2 Fuzzy of a of Figures 29 Two Band Image 32 ARTMAP Architecture Figure 5-3 Weight Vector Operation 33 Figure 5-4 Inter-ART Field Operation 34[r] ...
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Improving Video Classification Accuracy using Cloud
... video classification is desired, which could in turn be applied to content discovery and filtering Video classification is an inherently difficult task for various ...video classification is usually ...
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Development of Cardioid based graph ECG heart abnormalities classification technique
... abnormalities classification technique is ...classifier. Classification outcomes suggests that the proposed technique gives heart abnormality identification with a classification accuracy of ...
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Data Mining Decision Trees in Economy
... were run on Adult test data, all after removal of unknowns and using the original train/test split. The best performance of classification accuracy on test data is performed by FSS Naïve Bayes algorithm ...
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A Comparative Study of Different Machine Learning Algorithms on Gene Expression Profile Classification
... profiles classification, this paper compare the classification accuracy, run time and stability the of different machine learning algorithms including SVM, Decision tree, PNN, k-Nearest Neighbor, ...
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An approach for correcting inhomogeneous atmospheric effects in remote sensing images
... noting classification accuracy on the basis that an increase in classification accuracy reflects in improved image ...average accuracy of classification of a scene from Malaysia, ...
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Efficient sequential pattern mining algorithm and improved MFWC scheme for discovering complex disease and type-2 diabetes mellitus
... higher accuracy in ...k-NN accuracy (DKA) similar to LKA and GKA, but the K samples are selected from the uncertain ...of classification accuracy are computed, as shown in ...
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Fast web page categorization without the web page
... contents of the web page. Our implementation uses a two-step approach, in which a URL is first segmented into meaningful tokens, which are then analyzed as features for classification. We use a splitting method to ...
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Classification of Normal and Pathological Voice Using SVM and RBFNN
... on classification accuracy using Support Vector Machine and Radial Basis Func- tional Neural ...different classification models so as to compare different classifiers based on classification ...
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Impacts of sample design for validation data on the accuracy of feedforward neural network classification
... overall classification accuracy weight errors equally and could inflate the importance of rare classes while deflating that of abundant ...the accuracy assessment used in the validation could be ...
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Analytic Approach To Face Emotion Recognition With SVM Kernels
... for classification were extracted from the processed images such as the eyelids, cheeks, nose, eyebrows and ...using classification accuracy and classification time to identify the most ...
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Impact Analysis of Financial Early Warning Indicators Based on Random Forest
... the classification accuracy of the traditional random forest model is obtained, and then the important measure of each financial indicator is carried out from the traditional random forest ...the ...
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A comparative analysis on feature selection techniques for classification problems
... In this study, the experiments are conducted using seven datasets with and without feature selection methods. An evaluation of four feature subset methods with rank search (Correlation-based Attribute evaluation (CB), ...
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Quantification of Annual Urban Growth of Dar es Salaam Tanzania from Landsat Time Series Data
... accurate classification in the quantification of urban growth is very impor- tant for city planners and other ...annual classification map approach to improve the classification accuracy, for ...
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The impact of metadata on the accuracy of automated patent classification
... automated classification of ...their classification decisions solely on document text and ignore metadata (such as authors, publication date, and author ...the classification of patents into two ...
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Vol 7, No 9 (2017)
... extract classification features from CT ...give classification accuracy of ischemic stroke ...CSF classification accuracy 98.0%. The overall classification accuracy of ...
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