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Prepare pseudo random forest experiments

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Ricardo Montañana Gómez
2022-02-05 11:41:45 +01:00
parent 6da9b0cf07
commit f79df4b9c1
2 changed files with 26 additions and 2 deletions
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experiments/experiments.txt
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@@ -11,5 +11,29 @@
#ODTE_accuracy_slurm_0202_4.sh, ODTE&ODTE Random Forest linear-random&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"random\", \"max_features\": \"sqrt\"}"}
#ODTE_accuracy_slurm_0202_5.sh, ODTE&ODTE Random Forest rbf-trandom&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"rbf\", \"splitter\": \"trandom\", \"max_features\": \"sqrt\"}"}
#ODTE_accuracy_slurm_0202_6.sh, ODTE&ODTE Random Forest linear-trandom&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"trandom\", \"max_features\": \"sqrt\"}"}
# Pseudo Random Forest
ODTE&ODTE pseudo Random Forest rbf-best max_features-sqrt&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt" "be_hyperparams": "{\"kernel\": \"rbf\", \"splitter\": \"best\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest linear-best max_features-sqrt&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"best\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest rbf-random max_features-sqrt&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"rbf\", \"splitter\": \"random\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest linear-random max_features-sqrt&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"random\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest rbf-trandom max_features-sqrt&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"rbf\", \"splitter\": \"trandom\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest linear-trandom max_features-sqrt&{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"trandom\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest rbf-best max_samples-0.75&{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"rbf\", \"splitter\": \"best\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest linear-best max_samples-0.75&{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"best\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest rbf-random max_samples-0.75&{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"rbf\", \"splitter\": \"random\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest linear-random max_samples-0.75&{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"random\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest rbf-trandom max_samples-0.75&{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"rbf\", \"splitter\": \"trandom\", \"max_features\": \"sqrt\"}"}
ODTE&ODTE pseudo Random Forest linear-trandom max_samples-0.75&{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"linear\", \"splitter\": \"trandom\", \"max_features\": \"sqrt\"}"}
# kernel liblinear Random Forest and pseudo Random Forest
# RF
ODTE&ODTE Random Forest liblinear-best max_features-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"best\", \"multiclass_strategy\": \"ovr\"}"}'
ODTE&ODTE Random Forest liblinear-random max_features-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"random\", \"multiclass_strategy\": \"ovr\"}"}'
ODTE&ODTE Random Forest liblinear-trandom max_features-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"trandom\", \"multiclass_strategy\": \"ovr\"}"}'
# pseudo RF
ODTE&ODTE Random Forest liblinear-best max_samples-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"trandom\", \"multiclass_strategy\": \"ovr\"}"}'
ODTE&ODTE Random Forest liblinear-random max_samples-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"trandom\", \"multiclass_strategy\": \"ovr\"}"}'
ODTE&ODTE Random Forest liblinear-trandom max_samples-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_samples": 0.75, "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"trandom\", \"multiclass_strategy\": \"ovr\"}"}'
ODTE&ODTE Random Forest liblinear-best max_features-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"trandom\", \"multiclass_strategy\": \"ovr\"}"}'
ODTE&ODTE Random Forest liblinear-random max_features-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"trandom\", \"multiclass_strategy\": \"ovr\"}"}'
ODTE&ODTE Random Forest liblinear-trandom max_features-sqrt&'{"n_jobs": 10, "n_estimators": 100, "max_features": "sqrt", "be_hyperparams": "{\"kernel\": \"liblinear\", \"splitter\": \"trandom\", \"multiclass_strategy\": \"ovr\"}"}'

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experiments/hyperparams.xlsx
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