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To develop the students knowledge of Statistical learning techniques.
Introduction to statistical learning. Classification: logistic regression, LDA and QDA. Unsupervised learning: PCA, clustering methods. Resampling methods: cross-validation and the bootstrap. Linear Model selection and regularisation. Modelling with regression splines and smoothing splines. Tree-based methods. Support vector machines. Implementation in R.
ST644 is equivalent to ST464 (i.e. lectures and tutorials as for ST464).