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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 140 for “"classification algorithms"”.
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Instability of Decision Tree Classification Algorithms
Empirical results illustrate that the trees constructed by the proposed algorithm are more stable, noise-tolerant, informative, expressive, and concise. The proposed sensitivity measure can be used as a metric to evaluate the stability of splitting predicates. The tree sensitivity is an indicator …
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Brief Study of Classification Algorithms in Machine Learning
… of three most commonly used Machine Learning algorithms: k-Nearest Neighbors (kNN), Decision Trees and Naïve Bayes. All these algorithms fall under the Classification algorithm category of Unsupervised Machine Learning. This paper is constructed structurally in explaining the working theory …
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GS*. An Adaptive Bias Framework for Classification Algorithms
… adaptive bias in an algorithm for deriving classification rules from examples. Whereas prior studies examined either early setting of "global" biases for a specific problem taken as a whole (which learning method/algorithm is most appropriate to a finding a "cover" for a particular training …
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Performance analysis of text classification algorithms for PubMed articles
… of several different machine learning algorithms (Topic Modelling, Random Forest, Logistic Regression, Support Vector Classifiers, Multinomial Naive Bayes, Convolutional Neural Network and Long Short-Term Memory (LSTM)) in reproducing manually assigned MeSH annotations. Records for this …
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Comparison of accuracy and efficiency of five digital image classification algorithms
Accuracies and efficiencies of five algorithms for computer classification of multispectral digital imagery were assessed by application to imagery of three test sites (Roanoke, VA., Glade Spring, VA., and Topeka, KA.) A variety of land cover features and two types of image data (Landsat MSS and …
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The Effect of Dataset Size on the Performance of Classification Algorithms for Credit Scoring
… risk, the relative performance of different classification algorithms has received much attention by researchers. With the rise of machine learning techniques spurred on by fast, cheap computing and the generation and collection of massive datasets, there has been a great deal of research …
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Armband EMG-based Lifting Detection and Load Classification Algorithms using Static and Dynamic Lifting Trials
… task. Predictive or machine learning (ML) algorithms have been increasingly used in the ergonomics field to identify occupational risk factors, such as lifting loads. However, such algorithms are often developed and validated using the dataset collected from the same lab-based experimental …
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Extraction of vocal features for health assessment and early diagnosis - Effects of measurement uncertainty on classification algorithms
L'abstract è presente nell'allegato / the abstract is in the attachment
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Comparison of Classification Algorithms and Undersampling Methods on Employee Churn Prediction: A Case Study of a Tech Company
… before it is too late. Four different classification algorithms are tested on a variety of undersampled datasets in order to find the most effective undersampling and classification method for predicting employee churn. Statistical analysis is conducted on the appropriate evaluation …
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An analysis of the performance and interpretability of machine learning classification algorithms to predict long-term share returns on the JSE
… lack of research on the use of machine learning algorithms to predict long-term share returns on the Johannesburg Stock Exchange (JSE), with no studies that specifically examine the interpretability of machine learning algorithms. This study investigates the use of machine learning algorithms to …
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Performance analysis of automatic techniques for tissue classification in magnetic resonance images of the human brain
Classification of Magnetic Resonance (MR) images of the human brain into anatomically meaningful tissue labels is an important processing step in many research and clinical studies in neurology. The medical imaging research community is presented with a wide choice of classification algorithms from …
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Developing a Satellite-Based Methodology to Estimate Built-up Biocapacity for Use in the National Ecological Footprint and Biocapacity Accounts: A Comparative Study of Pléiades Neo and Sentinel-2 Imagery, Classification Algorithms, and Segmentation Approaches
… to compare the effect of spatial resolution, classification algorithm, and segmentation technique on the results. Multispectral imagery from Pléiades Neo (1.2-meter resolution) and Sentinel-2 (10-meter resolution) provided the basis for classification into land cover categories. Identified …
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AutoFE : efficient and robust automated feature engineering
… improves the performance of any traditional classification using an evolutionary algorithm. We demonstrate the effectiveness and robustness of our approach by conducting an extensive evaluation on 8 datasets and 5 different classification algorithms. We show that AutoFE can achieve an average …
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An Exploration of Multimodal Document Classification Strategies
This thesis explores multimodal document classification algorithms in a unified framework. Classification algorithms are designed to exploit both text and image information, which proliferates in modern documents. We design meta-classification schemes that combine and integrate state-of-the-art …
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Apklausų dalyvių aktyvumo analizė, pritaikant įvairius binarinio klasifikavimo algoritmus /
… The aim of this study was to test various binary classification algorithms to determine whether a survey response would be of high quality or not. To achieve this goal, five binary classification algorithms were selected: logistic regression, K-nearest neighbors, decision tree, support vector …
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Classification of semantic relations in different syntactic structures in medical text using the MeSH hierarchy
Two different classification algorithms are evaluated in recognizing semantic relationships of different syntactic compounds. The compounds, which include noun- noun, adjective-noun, noun-adjective, noun-verb, and verb-noun, were extracted from a set of doctors' notes using a part of speech tagger …
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Números complexos graduados e avaliação de desempenho de classificadores
Evaluate the performance of classification algorithms is not an easy task to be performed when considering several different criteria and the absolute numerical values are very close. Recently, in order to obtain more flexibility, a linguistic approach based in Fuzzy Complex Numbers for the …
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Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications
… feature extractors, feature selectors, and classification algorithms. In this work, we explore the different classification algorithms currently used in electroencephalographic (EEG) signal classification and assess their performance on intracranial EEG (iEEG) data. We first discuss the …
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Machine Learning Algorithms for Improved Glaucoma Diagnosis
… based on machine learning for automated classification of tests from visual field examinations and retinal nerve fibre measurements to detect glaucoma. Diagnostic performance of the applied machine learning classification algorithms was shown to depend primarily on the type of test …
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