Houses a series of projects I worked on for a course in Data Mining that I took in my Ph.D. Data Science program at UTEP in the Fall of 2022. Covers areas such as Regularized Logistic Regression, Optimization, Kernel Methods, PageRank Algorithm, Kernel PCA, Association Rule Mining, Anomaly Detection, Parametric/Nonparametric Nonlinear Regression, etc. All the PDF reports were directly generated in RMarkdown. The RMarddown files which contain the source codes are made available. Enjoy and come back for more ...
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Houses a series of projects I worked on for a course in Data Mining that I took in my Ph.D. Data Science program at UTEP in the Fall of 2022. Covers areas such as Regularized Logistic Regression, Optimization, Kernel Methods, PageRank, Kernel PCA, Association Rule Mining, Anomaly Detection, Parametric/Nonparametric Nonlinear Regression, etc.
Topics
anomaly-detection artificial-neural-networks association-rule-mining gam generalized-additive-models kernel-methods kernel-pca mars multivariate-adaptive-regression-splines nonparametric-nonlinear-regression pagerank parametric-nonlinear-regression projection-pursuit-regression random-forest regression regression-splines regularized smoothing-splines support-vector-machines
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