Usually, for applying ML algorithm, we are interested in the prediction rate and the FP
I'm interested in those, to know if we have got fit. but also, to find which are the most important features? which is the most important? which is the lowest? etc.
all on trained on the "quenched on first pericenter" label
BASIC RESULTS
Usually, for applying ML algorithm, we are interested in the prediction rate and the FP
I'm interested in those, to know if we have got fit. but also, to find which are the most important features? which is the most important? which is the lowest? etc.
DOD0 - Random Forst results DOD1 - present Hunga Bonga results DOD2 - present AutoScikitLearn results DOD3 - present AutoKeras results DOD4 - SHAP