"method_opts": {
'n_epochs': 300,
'model': 0, # 0 is avg, 1 is final
'burnin': 200
},
"metrics": {
'rmse': ivfunctions.mse,
'rsquare': ivfunctions.rsquare,
'raw': raw_metric
},
"plots": {
'print_metrics':
lambda x, y, z: papertables.paper_table(
x,
y,
z,
filename=
'many_z_many_t_nnet_print_metrics_paper_n_2000_gamma_6_n_z_10.csv',
nn=True)
},
"sweep_plots": {},
"mc_opts": {
'n_experiments': 100, # number of monte carlo experiments
"seed": 123,
},
"cluster_opts": {
"node_id": __NODEID__,
"n_nodes": __NNODES__
},
"proposed_method": "NystromRKHS",
}
'nstrm_n_comp': 100,
'shiv_L': 2,
'shiv_mon': None,
'lin_degree': 3
},
"metrics": {
'rmse': ivfunctions.mse,
'rsquare': ivfunctions.rsquare,
'raw': raw_metric
},
"plots": {
'print_metrics':
lambda x, y, z: papertables.paper_table(
x,
y,
z,
filename=
'many_z_one_t_print_metrics_paper_n_2000_gamma_6_n_z_10.csv',
nn=False)
},
"sweep_plots": {},
"mc_opts": {
'n_experiments': 100, # number of monte carlo experiments
"seed": 123,
},
"cluster_opts": {
"node_id": __NODEID__,
"n_nodes": __NNODES__
},
"proposed_method": "NystromRKHS",
}
"method_opts": {
'nstrm_n_comp': 100,
'shiv_L': 2,
'shiv_mon': None,
'lin_degree': 3
},
"metrics": {
'rmse': ivfunctions.mse,
'rsquare': ivfunctions.rsquare,
'raw': raw_metric
},
"plots": {
'print_metrics':
lambda x, y, z: papertables.paper_table(
x,
y,
z,
filename='one_z_one_t_nnet_print_metrics_paper_n_2000_gamma_8.csv',
nn=False)
},
"sweep_plots": {},
"mc_opts": {
'n_experiments': 100, # number of monte carlo experiments
"seed": 123,
},
"cluster_opts": {
"node_id": __NODEID__,
"n_nodes": __NNODES__
},
"proposed_method": "NystromRKHS",
}