Authors meeting decisions

[RaphaelS1]

2024-03-07

• Consider moving basic explanations of ML models to own chapter/Part of book
• Remove 'history' part of ML models and references and move to end of each chapter
• Describe ML models by classes and use one implementation as an example

2024-02-29

• https://github.com/mlsa-book/MLSA/issues/52

2024-01-11

2024-01-05

2023-12-22

• Maybe a 2e book include whole sections on Fairness and Interpretrability
• Make more explicit in concluding measures sections on Fairness and Interpretability with references to survival adaptations
• For OS version don't including CR measures but need to have for the book
• Add discussion about precision in scoring rule section and calibration section. Model can be well calibrated by have poor precision (e.g., KM is always well calibrated but not helpful for individual predictions). Ref countdown regression paper

2023-12-01

• Define 'features' and use that instead of 'covariates' everywhere
• Scope is right/left/interval-censoring and truncation
• Jan timeline feasible, both keep writing our sections then review when ready

2023-09-29

• Remove transparent/accessible classification everywhere
• Create online tool for tracking MLSA software that anyone can add to, add a snapshot of that into our Software chapter
• We will write exercises after book is finished and include one chapter at end called 'Exercises' divided into sections aligning with the book
• Agreed which chapters to include in Jan public repo deadline (https://github.com/RaphaelS1/MLSA/issues/12)

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2023-09-08

• @adibender @RaphaelS1 : Find notation to use throughout the book for ML and SA sections
• Agreed/agreeing on new table of contents (which will have lots of signposting)
• No bibliography workflow, just copy into the .bib
• Need to decide how much detail for individual model implementations

[adibender]

feature vs. covariate