def slow_gridminimise(learner, features, labels, params, measure=None):
from ..measures.nfoldcrossvalidation import nfoldcrossvalidation
if measure is None:
measure = np.trace
best_val = initial_value
best = None
for assignement in _allassignments(params):
_set_assignment(learner, assignement)
S,_ = nfoldcrossvalidation(features, labels, classifier=learner)
cur = measure(S)
if cur > best_val:
best = assignement
best_val = cur
return best
def slow_gridminimise(learner, features, labels, params, measure=None):
from ..measures.nfoldcrossvalidation import nfoldcrossvalidation
if measure is None:
measure = np.trace
best_val = initial_value
best = None
for assignement in _allassignments(params):
_set_assignment(learner, assignement)
S, _ = nfoldcrossvalidation(features, labels, classifier=learner)
cur = measure(S)
if cur > best_val:
best = assignement
best_val = cur
return best
def test_all_assignements():
assert len(list(_allassignments({'C': [0,1], 'kernel' : ['a','b','c']}))) == 2 * 3
def test_all_assignements():
assert len(list(_allassignments({
'C': [0, 1],
'kernel': ['a', 'b', 'c']
}))) == 2 * 3
