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 109 for “"Classification and regression"”.
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A learning hierarchy for classification and regression
… of variance (ANOVA) decompositions over GF(2) and R, as well as a general regression setup. For the problem of learning ANOVA decompositions, we obtain fundamental limits in the case of GF(2) under both sparsity and degree structures. We show how the degree or sparsity level is a useful measure …
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Deep neural network models for image classification and regression
… can be traced back mainly to the availability and the affordability of potential processing facilities, which were not widely accessible than just a decade ago for instance. Although it has demonstrated cutting-edge performance widely in computer vision, and particularly in object recognition …
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Accelerating research on 3D medical image classification and regression
Contains fulltext : 315690.pdf (Publisher’s version ) (Open Access)
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A generalised feedforward neural network architecture and its applications to classification and regression
… extensively used to model some important visual and cognitive functions. It equips neurons with a gain control mechanism that allows them to operate as adaptive non-linear filters. Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks where the basic synaptic …
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. The wide acceptance can be attributed to its robustness to high dimensionality problem. However, when the high-dimensional data is a sparse one, RF procedures are …
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Flächenhafte Schätzung mit Classification and Regression Trees und robuste Gütebestimmung ökologischer Parameter in einem kleinen Einzugsgebiet
… nicht oder nur mit unverhältnismäßig hohem Aufwand durch flächenhafte Aufnahmen und Messungen, z. B. mit Fernerkundungsverfahren ermitteln. Ihre räumliche Bereitstellung ist nur mit Hilfe von Schätzverfahren möglich. Manche Variablen lassen sich nicht mit modernen Interpolationsverfahren, wie z. …
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Performance Evaluation of Logistic Regression, Linear Discriminant Analysis, and Classification and Regression Trees Under Controlled Conditions
<p>Logistic Regression (LR), Linear Discriminant Analysis (LDA), and Classification and Regression Trees (CART) are common classification techniques for prediction of group membership. Since these methods are applied for similar purposes with different procedures, it is important to evaluate the …
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Using the classification and regression tree (CART) model for stock selection on the S&P 700
Traditionally, investment practitioners and academics alike have used stock fundamentals and a linear framework in order to predict future stock performance. This approach has been shown to have flaws as literature has shown that stock returns can exhibit non-linearity and involve complex relations …
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Topics in Tree-Based Methods
This work introduces methods and associated software for enhancing the interpretability of fitted models, with emphasis on classification and regression trees. We begin in Chapter 1 by describing novel techniques for growing classification and regression trees designed to induce visually …
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Integer optimization in data mining
… methods have been widely used in statistics and data mining over the last thirty years, integer optimization has had very limited impact in statistical computation. Thus, our objective is to develop a methodology utilizing state of the art integer optimization methods to exploit the discrete …
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Agricultural Land Use and the Eastern Cottontail in Illinois
… cottontail (Sylvilagus floridanus) in Illinois and (2) determine the movements, home range, and habitat selection of cottontails in an intensively farmed region of Illinois. The county level index for cottontail abundance was related to 13 agricultural land use variables for 1956-69 and 1982-89, …
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Foster Care Placement Decisions: Is Race a Factor
… administrative data were analyzed using logistic regression analysis and Classification and Regression Tree (CART) analysis. Data revealed that the number of investigator home visits, the number of other investigator contacts, the number of previous indicated allegations, and infancy were the …
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Clustering Response-Stressor Relationships in Ecological Studies
… encountered in water quality monitoring and ecological assessment. One concern for researchers and watershed resource managers is how the biological community in a watershed is affected by human activities. The conventional single model approach based on regression and logistic regression …
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Performance Analysis of Parallel Support Vector Machines on a MapReduce Architecture
… of the World Wide Web, the Internet of Things, and other digital technologies. As a result, data mining and machine learning algorithms face computational complexity issues when applied to real world datasets. Support Vector Machines (SVM) are powerful classification and regression tools but …
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Data mining occurrences of infectious diseases with SNOMED CT
… World Health Organization (WHO). Using simple Classification and Regression (CART), Bayes theory, and Best Fit trees, prediction algorithms are created based on the number of synonyms in infectious disease terms of SNOMED CT, the number of those diseases world-wide, the region of occurrence of …
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Support vector machine and its applications in information processing
… amounts of data being generated by businesses and researchers there is a need for fast, accurate and robust algorithms for data analysis. Improvements in databases technology, computing performance and artificial intelligence have contributed to the development of intelligent data analysis. The …
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Advanced AI techniques for comprehensive traffic incident analysis: enhancing incident duration prediction and accident risk forecasting
The progress of global urbanization and growth of vehicular traffic have led to an increase in traffic incidents, increasing demand for efficient modeling and prediction methodologies essential for traffic management. To meet this challenge, the thesis proposes the application of advanced machine …
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Some Advances in Classifying and Modeling Complex Data
… two of the most commonly used techniques are classification and regression modeling. As scientific technology progresses rapidly, complex data often occurs and requires novel classification and regression modeling methodologies according to the data structure. In this dissertation, I mainly …
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Application of Machine Learning Techniques for Real-time Classification of Sensor Array Data
… Neighbor (KNN), Support Vector Machine (SVM), Classification and Regression Trees (CART), Random Forest (RF), Naïve Bayes Classifier (NB), and Principal Component Regression (PCR). A total of 10 predictors that are associated with the response from 10 sensor channels are used to train and test …
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Spike-Based Classification of UCI Datasets with Multi-Layer Resume-Like Tempotron
… be applied to machine learning problems such as classification and regression. SNN are computationally more powerful per neuron than traditional neural networks. Though training time is slow on general purpose computers, spike-based hardware implementations are faster and have shown capability …
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