Analysis of consumer data – C4 – Who wants what? Clustering consumers using their product liking data (On Demand)

Data requirements and pre-processing. The two main techniques, Hierarchical Clustering (AHC) and K-Means Clustering explained and compared.

What this course will cover:

• Aim of the methods – data preprocessing. Agglomerative Hierarchical Classification (AHC) – how it works, which settings are best to use, deciding the number of clusters 
• KMEANS for larger data sets  – how it works 
• Comparison of the methods – recommendations
• Quick overview of other methods Latent Class, Fuzzy Clustering

This course is not a live session, but an on demand recording you can download instantly, that can then be worked through at your own pace, including workshops with datasets to practice and a certificate of completion at the end. If you wish to experience this as a live session, these are held periodically or you can contact us for a private booking.