MLFlow connection added

runs.txt

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+Cross validation baseline:
+python3 -m src.protocols_methodology.exp_cv --dataset adult --algo rf --n-folds 5 --seeds 0 1 2 3 4
+
+
+Bootstrap baseline:
+python3 -m src.protocols_methodology.exp_bootstrap --dataset adult --algo rf --n-bootstrap 30 --seeds 0 1 2 3 4
+
+
+Noise baseline:
+python3 -m src.protocols_methodology.exp_noise --dataset adult --algo rf --n-replicates 30 --noise-std 0.01 --seeds 0 1 2 3 4
+
+
+
+Small run: compute 0
+tmux new -s small
+python3 -m src.protocols_methodology.run_nsga_protocols --dataset adult --generations 3 --pop-size 8 --seed 0
+tmux attach-session -t small
+
+Medium run: compute 1
+tmux new -s medium
+python3 -m src.protocols_methodology.run_nsga_protocols --dataset adult --generations 10 --pop-size 24 --seed 0
+tmux attach-session -t medium
+
+Larger run: compute 3
+tmux new -s larger
+python3 -m src.protocols_methodology.run_nsga_protocols --dataset adult --generations 20 --pop-size 40 --seed 0
+tmux attach-session -t larger
+
+
+Send back:
+The three baseline summary csv files:
+runs/protocol_cv/__cv_summary.csv
+
+runs/protocol_bootstrap/__bootstrap_summary.csv
+
+runs/protocol_noise/__noise_summary.csv
+
+
+
+The three AutoML Pareto fronts:
+runs/_protocol_study/cv/pareto_front.csv
+
+runs/_protocol_study/bootstrap/pareto_front.csv
+
+runs/_protocol_study/noise/pareto_front.csv