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Attributes
During each phase of benchmarking there is different subset of available Attributes to use. User is free to change them as benchmark goes.
| Phase | Attributes available |
|---|---|
| Preprocessing | RUNS, X_RAW, Y_RAW, X, Y, STORE |
| Init Model | RUNS, X_RAW, Y_RAW, X, Y, MODEL, STORE |
| Train | X (selected), Y (selected), MODEL, STORE |
| Test | X (selected), Y (selected), MODEL, STORE |
| Evaluate | X (selected), Y (selected), Y_TRUE, MODEL, STORE |
| Summarize | X (all), Y (all), MODEL, STORE |
Attributes are implemented via simple Python map. This mean user can change them during runtime, however doing this reckless can cause falsified results.
To access attributes in any phase just use:
attributes[Attributes.X] = ....RUNS - number of folds that will be provided for train and test
X_RAW - raw X data read from .caddo file
Y_RAW - raw Y data read from .caddo file
X - processed X data
Y - processed Y data
MODEL - model to train and test
Y_TRUE - this is subset of Y provided exclusively to test function to compare it with Y predicted
STORE - this is python map() object, you can put there whatever you want and it will be passed through each step intact