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graph_denoising.sh
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graph_denoising.sh
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for dataset in toronto
do
for nn in 5 10 20 30 40 50 100 200 500 1000 1500 2000
do
for normalization in None BothSides
do
for graph_type in RBF
do
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn --minmaxscaler
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn --minmaxscaler --add_self_loops
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn --add_self_loops
done
done
done
done
for dataset in toronto
do
for nn in 5 10 20 30 40 50 100 200 500 1000 1500 2000
do
for normalization in None BothSides
do
for graph_type in RBF L2Distance
do
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn --minmaxscaler --nnk
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn --nnk
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn --minmaxscaler --add_self_loops --nnk
time python generate_graph.py --dataset $dataset --normalization $normalization --graph_type $graph_type --nn $nn --add_self_loops --nnk
done
done
done
done