def lfw_view2_random_AdaboostMixture(host, dbname, A):
trials = MongoTrials(
'mongo://%s:44556/%s/jobs' % (host, dbname),
exp_key=exp_keys['random'],
refresh=True)
bandit = MultiBandit()
mix = AdaboostMixture(trials, bandit, test_mask=True)
# XXX: Should the weights be used? I don't think so, we're basically
# doing LPBoost at this point
specs, weights, tids = mix.mix_models(int(A), ret_tids=True)
assert len(specs) == len(tids)
namebases = []
for spec, tid in zip(specs, tids):
# -- allow this feature cache to be
# reused by AdaboostMixture and
# SimpleMixtures of different
# sizes
#XXX: Potentially affected by the tid/injected jobs bug,
# but unlikely. Rerun just in case once dual svm solver is in.
namebase = '%s_%s' % (dbname, tid)
namebases.append(namebase)
get_view2_features(
slm_desc=spec['model']['slm'],
preproc=spec['model']['preproc'],
comparison=spec['comparison'],
namebase=namebase,
basedir=os.getcwd(),
)
basedirs = [os.getcwd()] * len(namebases)
train_view2(namebases=namebases, basedirs=basedirs)
def lfw_view2_final_get_mix(host='honeybadger.rowland.org',
dbname='final_random',
A=100):
trials = MongoTrials(
'mongo://%s:44556/%s/jobs' % (host, dbname),
exp_key=exp_keys['random'],
refresh=True)
return trials
bandit = MultiBandit()
simple_mix = SimpleMixture(trials, bandit)
simple_mix_trials = simple_mix.mix_trials(int(A))
ada_mix = AdaboostMixture(trials, bandit)
ada_mix_trials = ada_mix.mix_trials(int(A))
return simple_mix_trials, ada_mix_trials