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Page Content

WEB SESSION

1/2 Dec 2020

Non-Life Pricing&Profitability Analysis Using ML Techniques with R

Tuesday, 01 December 2020

  1. 09:00 - 10:45 Data Selection, Pre-Analysis and Feature Selection (data quality, pre-treatment, missing values, feature engineering and feature selection)
  2. Overfitting and cross-validation
  3. Case study: Data Analysis and filtering
  4. 10:45 - 11:00 Coffee Break
  5. 11:00 - 12:30 Reminders and Q&A about supervised learning models
  6. 12:30 - 13:30 Lunch
  7. 13:30 - 14:30 Example: Fitting a regression tree and random forest on frequency
  8. Presentation: Case Study: Regression tree and random forest model adjustment for frequency and cost
  9. Presentatition Case study: Reminders and Q&A about supervised learning models
  10. 14:30 - 16:00 Participants work by themselves on the case studies (individual support available thanks to Teams meeting)
  11. 16:00 - 17:00 Correction of the case studies and closing of the day

Wednesday, 02 December 2020

  1. 09:00 - 10:00 Interpretability of Machine learning techniques
  2. Case study: Features selection, partial dependence plot and Shapley Value
  3. Case study: Application of GBM method to highlight interactions
  4. 10:00 - 11:00 Participants work by themselves on the case studies (individual support available thanks to Teams meeting)
  5. 11:00 - 12:00 Correction of the case studies
  6. 12:00 - 13:00 Lunch
  7. 13:00 - 14:00 Reminder and example about unsupervised machine learning
  8. 14:00 - 14:15 Break
  9. 14:15 - 15:30 Profitability and Competition analysis (profitability and positioning assessment, reverse engineering of competitors prices)
  10. Example: profitability analysis with regression trees
  11. (Time zone: CET - Central European Time)
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