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 5 of 5 for “"tree support"”.
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Apklausų dalyvių aktyvumo analizė, pritaikant įvairius binarinio klasifikavimo algoritmus /
… regression, K-nearest neighbors, decision tree, support vector machine, and XGBoost classifiers. The best results were obtained using the XGBoost classifier, with oversampling applied to the training dataset. The best model achieved a sensitivity (recall) metric of 82 % and a specificity of …
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Phylogenetic utility of mitochondrial and nuclear genes: a case study in the diptera (true flies)
… sample of dipteran species. For phylogenetic tree reconstruction, mitochondrial genes performed generally inferior to nuclear genes. However, the mitochondrial genes resolved branches for which nuclear genes failed. Moreover, the combined use of mitochondrial and nuclear sequences produced …
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Examination of machine learning methods for multi-label classification of intellectual property documents
… increased the overall performance of Decision Tree, Support Vector Machine, Logistic Regression, and Neural Net models. It was further found that some classifiers trained on data not subject to principal component analysis showed decreasing performance metrics with increasing data sizes.
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Efficacy and Effect of Tree Stabilization Systems On Landscape Tree Growth and Establishment
… anchoring are used to prevent post-transplant tree destabilization in the landscape, but little scientific evidence exists to support this practice. This experiment tested the efficacy of three generic tree stabilization systems (TSS) and their effect on tree growth and establishment. In spring …
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Recognizing cardiovascular disease patterns with machine learning using NHANES accelerometer determined physical activity data
… of the data. In general, the lasso regression, support vector machines (SVM) and random forest (RF) classifiers all performed well on large sets of data-driven features, achieving greater than 82% classification accuracy when time spent in PA intensity categories was combined with k-means and …