Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 441 for “"Classification Accuracy"”.
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Geographic information system strategies for improving Landsat land use classification accuracy
… System strategies for improving the land use classification and mapping accuracies of Landsat multi spectral scanner (MSS) data. The specific strategies are additional-band, class reduction, exclusion, and conditional. Three classified images served as the basis upon which all accuracy …
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The Relationship of MMPI-A Item Effectiveness to Item Content, Diagnostic Category, and Classification Accuracy
<p>Archer, Handel, and Lynch (2001) recently compared the item endorsement frequencies for the MMPI-A normative sample against two adolescent clinical samples. Results showed that the MMPI-A contains a substantial number of items that do not show a significant difference in item endorsement …
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Examining the Classification Accuracy of the Social, Academic, Emotional Behavior Risk Screener and Its Relationship with Writing Performance
… under the ROC curve for CBM-WE revealed fair accuracy (AUC = .761; 95% Confidence Interval [.644, .878]) and poor accuracy was noted for the SAEBRS (AUC = .653; 95% Confidence Interval [.528, .778]). Although there was no statistically significant difference between the independent AUC values, …
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Detection of Attribute Hierarchies and Classification Accuracy: the Value of the Hierarchical Diagnostic Classification Model in Formative Assessment Practices
… hierarchy is not present influences the classification accuracy of the models. This study was designed to evaluate the efficiency of the HDCM in statistically testing for an attribute hierarchy, therein providing researchers with evidence and support for subsequent model application. By …
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A Comparison of the Classification Accuracy of Linear and Quadratic Statistical Discriminant Models versus Linear and Quadratic Programming Discriminant Models
… purpose of this research was to compare the classification accuracy of two mathematical programming models versus traditional statistical discriminant analysis. Monte Carlo techniques were used to compute population 1, population 2, and average misclassification rates for the linear …
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The Behavior Assessment System for Children Third Edition (BASC-3)’s Classification Accuracy for Attention-Deficit/Hyperactivity Disorder (ADHD) in Young Adults
… The purpose of this study was to determine the classification accuracy of the <em>Behavior Assessment System for Children</em> (Third Ed.; BASC-3) Inattention/Hyperactivity composite <em>t</em>-score in predicting the diagnosis of Attention-Deficit/Hyperactivity Disorder among college students …
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Heuristic Weighted Voting
… can have a significant impact on the overall classification accuracy an ensemble is able to achieve. With some methods, the ensemble cannot even achieve as high a classification accuracy as the most accurate individual classifying component. To address this issue, we present the strategy of …
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Improving Neural Network Classification Training
… of general methods for improving neural network accuracy on classification tasks, grouped under the label of classification-based methods. The central theme of these approaches is to provide problem representations and error functions that more directly improve classification accuracy than …
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Entropy aided RF-DNA fingerprint learning from Gabor-based images
… Convolutional Neural Network (CNN). While the classification accuracy has been improved from using raw signals learning the amount of data generated is large and computationally expensive. This work investigate the usage of statistical thresholds like entropy applied to ”tiles” selected from …
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Improving Identification of Area Targets by Integrated Analysis of Hyperspectral Data and Extracted Texture Features
… spectral data and extracted texture features on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the VNIR-SWIR portion of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the …
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An object-based image analysis approach for detecting urban impervious surfaces
… have proven to be unsuitable for automated classification because of its high spectral variability and complex land covers in urban areas. Accurate and rapid classification of impervious surfaces would help in emergency management after extreme events like flooding, earthquakes, fires, …
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Machine learning classification techniques for non-intrusive load monitoring
… In this thesis, existing machine learning classification techniques are reviewed within the context of the non-intrusive load monitoring application. A non-intrusive load monitoring algorithm is developed in this to extract the prominent hidden features contained within the electrical …
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Neuroimaging metrics of externalizing disorders: assessing neurobiological features of substance use, withdrawal, substance use disorders, and psychopathy
… psychopathic traits. However, variability in the classification accuracy of ML models precludes inferences of how well neuroimaging metrics can distinguish externalizing patients and controls. Moreover, variability in the classification accuracy of ML models and the lack of work using modalities …
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Effective Features and Machine Learning Methods for Document Classification
Document classification has been involved in a variety of applications, such as phishing and fraud detection, news categorisation, and information retrieval. This thesis aims to provide novel solutions to several important problems presented by document classification. First, an improved Principal …
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Classifying drug-induced epileptic seizures in zebrafish larvae
… epilepsies. In this project, a mathematical classification model was created with the aim of correctly classifying zebrafish larvae having an (PTZ induced) epileptic seizure. The model also computes biomedical parameters describing behavioural attributes of the larvae. Several data mining …
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Analysis and techniques for non-intrusive appliance load monitoring.
… Wavelet functions can significantly affect the classification accuracy. Among the four wavelets investigated in this thesis, two wavelets (Daubechies and Symlets) are able to provide the highest mean classification accuracy.
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Classification of stop consonant place of articulation
… to separate the three places is evaluated by the classification error based on the distributions of its values for the three places, and another quantifier based on F-ratio. These two quantifiers generally agree and show how well each individual attribute separates the three places. Combinations …
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An Extended Local Binary Pattern for Gender Classification
… an efficient gender recognition system with high classification accuracy. In this regard, we proposed a novel local binary descriptor capable of extracting more informative and discriminative local features for the purpose of gender classification. We have evaluated our approach on the standard …
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