The Statistical Computing and Data Visualisation Section is now offering tutorials.
Visualising high-dimensional data presented by Di Cook
This is for scientists and data science practitioners who regularly work with high-dimensional data and models and are interested in learning how to better visualise them. You will learn about recognising structure in high-dimensional data, including clusters, outliers, non-linear relationships, and how this can be used with methods such as supervised classification, cluster analysis and non-linear dimension reduction. The course will be structured as follows:
1:00-1:20 Introduction: What is high-dimensional data, why visualise and overview of methods
1:20-1:45 Basics of linear projections, and recognising high-d structure
1:45-2:30 Effectively reducing your data dimension, in association with non-linear dimension reduction
2:30-3:00 BREAK and PRACTICAL EXERCISES
3:00-3:45 Understanding clusters in data using visualisation
3:45-4:30 Building better classification models with visual input
About the presenter: Dianne Cook is Professor of Business Analytics at Monash University in Melbourne, Australia. She is a world leader in data visualisation, especially the visualisation of high-dimensional data using tours with low-dimensional projections, and projection pursuit. She is currently focusing on bridging the gap between exploratory graphics and statistical inference. Di is a Fellow of the American Statistical Association, past editor of the Journal of Computational and Graphical Statistics, current editor of the R Journal, elected Ordinary Member of the R Foundation, and elected member of the International Statistical Institute.
Background: Participants should have a good working knowledge of R, and some background in multivariate statistical methods and/or data mining techniques.
More details can be found at https://statsocaus.github.io/tutorial_highd_vis/. Materials will be provided a few days prior to the tutorial.
Cancellation Policy
Occasionally courses have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.
Cancellations received prior to two weeks before the event will be refunded, minus a $25 administration fee. From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au.
For any questions, please email events@statsoc.org.au
@StatSocAus
