Introduction to Statistical Learning (Data Mining I)
Date:
22/01/2018 - 23/01/2018
Organised by:
Lancaster University
Presenter:
Professor Brian Francis
Level:
Entry (no or almost no prior knowledge)
Contact:
Angela Mercer 01524 593064, psc@lancaster.ac.uk
Map:
View in Google Maps (LA1 4YF)
Venue:
Department of Mathematics and Statistics
C/o Postgraduate Statistics Centre
Lancaster University
Lancaster
Description:
This course introduces the concepts of statistical learning focusing on predictive models.
It covers modern statistical modelling methods, including logistic regression, multinomial regression, and classification and regression trees, as well as assessment methods such as prediction error, deviance and AUC. The focus will be on validation and cross-validation methods, to ensure that selected models are not overfitting the data. Real life examples are used, and there is time for practical use of the methods described using the R package.
Cost:
External from industry/Commerce, £540 and External from academic institution/public sector/charity staff £460; External postgraduate student £300.
Website and registration:
www.lancaster.ac.uk/maths/postgraduate/short-courses/
Region:
North West
Keywords:
Data Mining
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