Analysis of consumer data – C13 – Predicting product performance from existing data using machine learning methods – Partial Least Squares (PLS) modelling

Product code: Product Optimisation

Remote training

March 13, 2025 - March 13, 2025

Virtual option available

Technique to build models to predict one block of correlated data from another. Applications covered include models to predict liking (from sensory/analytic data) or to predict sensory from instrumental/analytic data.

What this course will cover:

  • PLS – how it works explained graphically 
  • Interpretation and application of key statistics (VIP, Q2)   
  • How to build a model selection strategy  
  • Application to linking liking and product characteristics (Sensory/ instrumental/ analytic) 
  • Issues to consider when predicting liking of future samples 

Pre-requisite: familiarity with PCA Module 3 and regression module 2 

This course is a live session, but a recording can also be purchased afterwards. Please contact us.

Select currency

$261.56 (Excluding any applicable taxes)

Other course information

Software

You will need the latest version of XLSTAT installed on your computer. If you don’t have a licence you can download a 14-day trial version.

Timing

Each module is 2 hours.

Start time 10am GMT

Please check your time zones to make sure the timings are suitable for your country

 

Prices

Each Module: £200.00 ex VAT

Discounts

For every five modules purchased, only pay for four

Academic Delegate discount is available.

 

Please contact us for more details.