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overall accuracy

Hyperspectral Image Classification  Based on Hierarchical SVM  Algorithm for Improving  Overall Accuracy

Hyperspectral Image Classification Based on Hierarchical SVM Algorithm for Improving Overall Accuracy

... classification accuracy of HSI remote sensing images de- pend on the number of classes, features, training data as well as the kernel func- ...tion. Overall classification accuracy is reduced by ...

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Evaluation of Feature Subset Selection, Feature Weighting, and Prototype Selection for Biomedical Applications

Evaluation of Feature Subset Selection, Feature Weighting, and Prototype Selection for Biomedical Applications

... best overall accuracy while decision tree in- duction exhibits the worst ...good accuracy might be due to the fact that the classifier can classify excellently the classes with large sample number ...

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Supervised Material Classification in Oblique Aerial Imagery Using Gabor Filter Features

Supervised Material Classification in Oblique Aerial Imagery Using Gabor Filter Features

... its overall accuracy, the individual class accuracies, its ability to incorporate diverse training data, and finally the quantity of training data necessary to produce acceptable ...of accuracy or ...

107

Jute and Tea Discrimination through
 Fusion of SAR and Optical Data

Jute and Tea Discrimination through Fusion of SAR and Optical Data

... An overall accuracy of 85% with accuracy of 86% for jute, 79% for tea, 78% for forests and 96% for fallow was obtained based on maximum likelihood ...

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Effects of disease severity distribution on the performance of quantitative diagnostic methods and proposal of a novel ‘V-plot’ methodology to display accuracy values

Effects of disease severity distribution on the performance of quantitative diagnostic methods and proposal of a novel ‘V-plot’ methodology to display accuracy values

... per-range accuracy against Chol gold can be immediately derived and compared with the previously published V-plot of Chol rapid ...of overall accuracy may not be directly compared if samples are ...

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Identification of the rumination in cattle using support vector machines with motion-sensitive bolus sensors

Identification of the rumination in cattle using support vector machines with motion-sensitive bolus sensors

... Abstract: The reticuloruminal function is central to the digestive efficiency in ruminants. For cattle, collar- and ear tag-based accelerometer monitors have been developed to assess the time spent ruminating on an ...

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Classification of Suncus murinus species complex (Soricidae: Crocidurinae) in Peninsular Malaysia using image analysis and machine learning approaches

Classification of Suncus murinus species complex (Soricidae: Crocidurinae) in Peninsular Malaysia using image analysis and machine learning approaches

... The approach described here is simple and permits a reliable identification of the S. murinus species population. Even though features used in this study are simple as pro- vided in MATLAB, they have significance in ...

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Named Entity Recognition System for Punjabi Language Text using Hybrid Approach

Named Entity Recognition System for Punjabi Language Text using Hybrid Approach

... the overall accuracy of the system and to increase the corpus size and to increase the number of rules like animal/bird name rule, direction name rule, measurement named rule, transport or vehicle named ...

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Fully Automated Coronal and Sagittal Chest Segmentation using Colour Features and Fuzzy C-Means Clustering in CT Images

Fully Automated Coronal and Sagittal Chest Segmentation using Colour Features and Fuzzy C-Means Clustering in CT Images

... the overall accuracy of segmenting lung parenchyma from the Coronal and Sagittal Chest CT images by reducing the error of segmentation present in methodologies proposed ...and accuracy of the ...

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An Effective Approach for Cyberbullying Detection and avoidance

An Effective Approach for Cyberbullying Detection and avoidance

... Rules based on a dictionary of key words are used to classify a window of posts. The overall accuracy is 58.63% was prosed in [3].The Lexical Syntactic Feature (LSF) architecture to detect offensive content ...

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Impacts of sample design for validation data on the accuracy of feedforward neural network classification

Impacts of sample design for validation data on the accuracy of feedforward neural network classification

... way overall accuracy is typically estimated with a validation sample, it is hypothesized that the overall accuracy of the final classification, evaluated using the testing set, will be larger ...

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EVALUATION OF THE ROLE OF BEDSIDE LUNG ULTRASOUND VERSUS CHEST X-RAY IN CRITICALLY ILL PATIENTS

EVALUATION OF THE ROLE OF BEDSIDE LUNG ULTRASOUND VERSUS CHEST X-RAY IN CRITICALLY ILL PATIENTS

... and overall accuracy to highly comparable results with chest computed ...and accuracy of chest ultrasound increased with time and with number of ...

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Development and performance of a diagnostic/prognostic scoring system for breakthrough pain

Development and performance of a diagnostic/prognostic scoring system for breakthrough pain

... • Set the thresholds and evaluate the classification perfor- mances. The thresholds among contiguous classes can be derived either by using the decision rule in Equation (5) or by using a post hoc analysis on each ...

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AN EMPIRICAL EVALUATION FOR THE INTRUSION DETECTION FEATURES BASED ON MACHINE 
LEARNING AND FEATURE SELECTION METHODS

AN EMPIRICAL EVALUATION FOR THE INTRUSION DETECTION FEATURES BASED ON MACHINE LEARNING AND FEATURE SELECTION METHODS

... of accuracy are fallen short due to poor image resolution, noise, and distinction between cancerous and non-cancerous tumours is very ...image accuracy based on this framework, after new method has been ...

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Advanced Investigation of Remote Sensing to Geological Mapping of Zefreh Region in Central Iran

Advanced Investigation of Remote Sensing to Geological Mapping of Zefreh Region in Central Iran

... DOI: 10.4236/ojg.2017.710101 1510 Open Journal of Geology gion includes consists of the igneous, sedimentary and metamorphic. Various types of igneous rocks including tonalite, gabbro and diorite have infiltrated to the ...

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TnT – A Statistical Part of Speech Tagger

TnT – A Statistical Part of Speech Tagger

... The table shows the percentage of unknown tokens, separate accuracies and standard deviations for known and unknown tokens, as well as the overall accuracy... percentage unknowns 11.9%.[r] ...

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Comparative evaluation of the diagnostic efficacy of conventional film radiography and direct digital radiography for detection of periapical lesions

Comparative evaluation of the diagnostic efficacy of conventional film radiography and direct digital radiography for detection of periapical lesions

... For ROC curve analysis technique, our results were in accordance with an in vivostudy by Parihar et al. 12 where ROC curve was used to check the diagnostic accuracy of the different techniques. The overall ...

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Predicting Student Performance in Higher Education Institutions Using Decision Tree Analysis

Predicting Student Performance in Higher Education Institutions Using Decision Tree Analysis

... We aim to analyze collective student information through a questionnaire (based on LimeSurvey and Google Form) as well as classify the collected data to predict and categorize student performance. We also seek to ...

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Ontology Aware Token Embeddings for Prepositional Phrase Attachment

Ontology Aware Token Embeddings for Prepositional Phrase Attachment

... Type-level word embeddings use the same set of parameters to represent all instances of a word regardless of its context, ignor- ing the inherent lexical ambiguity in lan- guage. Instead, we embed semantic con- cepts (or ...

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Comparing Software Cost Estimation Using Scott-Knott Test

Comparing Software Cost Estimation Using Scott-Knott Test

... ABSTRACT: Software cost Estimation is the approximate judgement of the costs for a project. It is to predict the most realistic effort needed to complete a software project. Accurate effort prediction is done by ...

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