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View Code? Open in Web Editor NEWCheat Sheets for mlr3 and Friends
Home Page: https://cheatsheets.mlr-org.com/
Cheat Sheets for mlr3 and Friends
Home Page: https://cheatsheets.mlr-org.com/
Use knitr
or the minted
package for highlighted and easy copyable R code.
Cheatsheets usually contain no hyperlinks as one of their main purposes is the printed version (i.e. the "mlr3book" link and "mlr-org" link)
Use grey background for inline code formatting, e.g. mlr task
is hard to distinguish between code and normal text
replace www.mlr-org.com by https://mlr-org.com
reduce header height for more content space?
Change font to roboto
"The mlr3 package provides R6 classes for the essential
building blocks of this machine learning workflow:"
Rather than starting all listings with "A [...]" just do "Task: Encapsulates [...]"
maybe "encapsulates" is too techy here, rephrase?
color the workflow boxes? Replace workflow figure
"If you simply provide the dataset, it is automatically We do not have space for this. I removed this part completely. I think this is not of interest for the normal user.
converted to a DataBackendDataTable." -> The default backend is "DataBackendDataTable".
Then, list all other available backends in a list?
Before starting with code, add a heading like "examples"
TaskRegr$newt(backend, target)
<- typo
"For classification, the name of the target column is a label with only few distinct values." -> sounds more special than it is. Maybe just write something like "for classif, target
is a character vectors with representing class labels"?
Rather than showing all methods, show the output of an example task? There are too many methods for a task and it gets boring quite quickly. Also all of this is in more detail in the help page whereas the output of a created task is not.
Show mlr_learners dictionary? Replace all dictionaries with sugar
Mention and link to mlr3learners org and custom learners?
"Get learner by key and construct the learner with specific
hyperparameter and settings (...) in one go." -> Do not show a generic way but rather a concrete example.
"Resampling is used to assess the performance of a learning algorithm." -> mention "cross-validation" somewhere here
shortly explain the difference/similarity between resample/cross-validation
mention that multiple train&predict calls are done during resampling
Remove expand_grid()
I know, not much space left, but maybe also show the output of a BMR?
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