Essays about: "Comparison of Automatic Classifiers"
Showing result 1 - 5 of 7 essays containing the words Comparison of Automatic Classifiers.
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1. Sequential Deep Learning Models for Neonatal Sepsis Detection : A suitability assessment of deep learning models for event detection in physiological data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Sepsis is a life-threatening condition that neonatal patients are especially susceptible to. Fortunately, improved bedside monitoring has enabled the collection and use of continuous vital signs data for the purpose of detecting conditions such as sepsis. READ MORE
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2. Automatic Diagnosis of Parkinson’s Disease Using Machine Learning : A Comparative Study of Different Feature Selection Algorithms, Classifiers and Sampling Methods
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Over the past few years, several studies have been published to propose algorithms for the automated diagnosis of Parkinson’s Disease using simple exams such as drawing and voice exams. However, at the same time as all classifiers appear to have been outperformed by another classifier in at least one study, there appear to lack a study on how well different classifiers work with a certain feature selection algorithm and sampling method. READ MORE
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3. A comparison of machine learning algorithms for automatic classification of neurons by their morphology
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Classification of neurons has been a studied topic in neuroscience for several years and with the increase of data, new methods are encouraged to help with the classification. This study compares different machine learning algorithms to see which are better suited for classification of large data sets of morphological reconstructions in multidimensional feature space. READ MORE
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4. Improving Artist Content Matching with Stacking : A comparison of meta-level learners for stacked generalization
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Using automatic methods to assign incoming tracks and albums from multiple sources to artists entities in a digital rights management company, where no universal artist identifier is available and artist names can be ambiguous, is a challenging problem. In this work we propose to use stacked generalization to combine the predictions of heterogeneous classifiers for an improved quality of artist content matching on two datasets from a digital rights management company. READ MORE
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5. Speech act classification : A comparison of algorithms for classifying out of context utterances with DAMSL
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : With the growing of everyday automation the need for better speech understanding in machines increases. A unsolved problem in speech processing is the automatic recognition of speech acts. A speech act is a utterance which fills a function in the communication. READ MORE
