A 2 day course: 5th & 6th February 2018
This course develops the concepts of statistical learning introduced in the first course on Statistical Learning.
It covers both clustering (unsupervised learning) and advanced prediction (supervised learning) methods.
The focus will be on methods which have a statistical interpretation, so model-based clustering through latent class analysis will be covered along with more heuristic methods. Real life examples are used, and there is time for practical use of the methods described using the R and Latent Gold packages.
Important please note:
If the course is fully booked please do complete the registration, as then you will be placed on a waiting list. You will be allocated a place if more places become available or if people cancel.
We will make every attempt to accommodate Lancaster University staff and postgraduate research students on our courses. However, if a course becomes fully booked we reserve the right to give priority to students on the MSc in Statistics, MSc in Data Science, and external participants.
Details of course fees.
Registrations are transferable to another course or individual at any time. Full refunds will be given for cancellation 10 or more working days before the course start date. Otherwise the full course fee will be charged.
Introduction to clustering
Hierarchical and non-hierarchical clustering
Distance metrics and types of linkage
Assessment of clustering performance.
Latent class models.
Longitudinal latent class models.
Other predictive methods