Random Search in hyperparam

This commit is contained in:
Petrônio Cândido 2019-12-26 08:05:35 -03:00
parent ad1205121d
commit 87a50c1342
3 changed files with 20 additions and 18 deletions

View File

@ -365,42 +365,46 @@ def mutation_random_search(individual, **kwargs):
:param pmut: individual probability o
:return:
"""
import copy
new = copy.deepcopy(individual)
vars = kwargs.get('variables', None)
tvar = kwargs.get('target_variable', None)
l = len(vars)
il = len(individual['explanatory_variables'])
il = len(new['explanatory_variables'])
#
if il > 1:
for l in range(il):
il = len(individual['explanatory_variables'])
il = len(new['explanatory_variables'])
rnd = random.uniform(0, 1)
if rnd > .5:
rnd = random.randint(0, il-1)
val = individual['explanatory_variables'][rnd]
individual['explanatory_variables'].remove(val)
individual['explanatory_params'].pop(rnd)
if rnd < il and il > 1:
val = individual['explanatory_variables'][rnd]
new['explanatory_variables'].remove(val)
new['explanatory_params'].pop(rnd)
else:
rnd = random.randint(0, l-1)
while rnd in individual['explanatory_variables']:
while rnd in new['explanatory_variables']:
rnd = random.randint(0, l-1)
individual['explanatory_variables'].append(rnd)
individual['explanatory_params'].append(random_param(vars[rnd]))
new['explanatory_variables'].append(rnd)
new['explanatory_params'].append(random_param(vars[rnd]))
for ct in np.arange(len(individual['explanatory_variables'])):
for ct in np.arange(len(new['explanatory_variables'])):
rnd = random.uniform(0, 1)
if rnd > .5:
mutate_variable_params(individual['explanatory_params'][ct], vars[ct])
mutate_variable_params(new['explanatory_params'][ct], vars[ct])
rnd = random.uniform(0, 1)
if rnd > .5:
mutate_variable_params(individual['target_params'], tvar)
mutate_variable_params(new['target_params'], tvar)
individual['f1'] = None
individual['f2'] = None
new['f1'] = None
new['f2'] = None
return individual
return new
def mutate_variable_params(param, var):

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@ -66,9 +66,7 @@ def execute( dataset, **kwargs):
new[key] = ret[key]
new_stat[key] = ret[key]
print(new)
if new['f1'] <= individual['f1'] and new['f2'] <= individual['f2']:
if new['f1'] < individual['f1'] or (new['f1'] == individual['f1'] and new['f2'] < individual['f2']):
individual = new
no_improvement_count = 0
stat[i] = new_stat

View File

@ -58,7 +58,7 @@ target_variable = {'name': 'Load', 'data_label': 'load', 'type': 'common'}
nodes=['192.168.28.38']
deho_mv.random_search(datsetname, dataset,
ngen=200, mgen=200,
ngen=200, mgen=70,
window_size=2000, train_rate=.9, increment_rate=1,
experiments=1,
fts_method=wmvfts.WeightedMVFTS,