Thesis-NoiseDetection-26-attributes/run_surrogate_rendering.sh

#! /bin/bash

# default param
ILS=10000
LS=100
SS=50
LENGTH=32 # number of features
POP=100
ORDER=2
TRAIN_EVERY=50


#output="rendering-attributes-ILS_${ILS}-POP_${POP}-LS_${LS}-SS_${SS}-SO_${ORDER}-SE_${TRAIN_EVERY}"
DATASET="rnn/data/datasets/features-selection-rendering-scaled/features-selection-rendering-scaled"

for POP in {20,60,100};
do
    for ORDER in {2,3};
    do
        for LS in {1000,5000,10000};
        do
            output="rendering-attributes-POP_${POP}-LS_${LS}-SS_${SS}-SO_${ORDER}-SE_${TRAIN_EVERY}"
            echo "Run optim attributes using: ${output}"
            python find_best_attributes_surrogate.py --data ${DATASET} --start_surrogate ${SS} --length 30 --ils ${ILS} --ls ${LS} --pop ${POP} --order ${ORDER} --train_every ${TRAIN_EVERY}  --output ${output}
        done
    done
done