def learners():
kwargs = dict(event_size=EVENT_SIZE, outcome_size=OUTCOME_SIZE)
for klass in ("Perceptron", "AveragedPerceptron"):
factory = getattr(perceptron, klass)
yield (klass, " vanilla ", factory(**kwargs))
for d in DEGREES:
yield (klass, "polynomial-%d" % d, factory(kernel=perceptron.polynomial_kernel(d), **kwargs))
for g in GAMMAS:
yield (klass, "radial-%.3f" % g, factory(kernel=perceptron.radial_basis_kernel(g), **kwargs))
for b in BEAM_WIDTHS:
yield ("SparseAveragedPerceptron", "beam-%d" % b, perceptron.SparseAveragedPerceptron(beam_width=b, **kwargs))
def learners():
kwargs = dict(event_size=EVENT_SIZE, outcome_size=OUTCOME_SIZE)
for klass in ('Perceptron', 'AveragedPerceptron'):
factory = getattr(perceptron, klass)
yield (klass, ' vanilla ', factory(**kwargs))
for d in DEGREES:
yield (klass,
'polynomial-%d' % d,
factory(kernel=perceptron.polynomial_kernel(d), **kwargs))
for g in GAMMAS:
yield (klass,
'radial-%.3f' % g,
factory(kernel=perceptron.radial_basis_kernel(g), **kwargs))
for b in BEAM_WIDTHS:
yield ('SparseAveragedPerceptron',
'beam-%d' % b,
perceptron.SparseAveragedPerceptron(beam_width=b, **kwargs))
def learners():
kwargs = dict(event_size=EVENT_SIZE, outcome_size=OUTCOME_SIZE)
for klass in ('Perceptron', 'AveragedPerceptron'):
factory = getattr(perceptron, klass)
yield (klass, ' vanilla ', factory(**kwargs))
for d in DEGREES:
yield (klass, 'polynomial-%d' % d,
factory(kernel=perceptron.polynomial_kernel(d), **kwargs))
for g in GAMMAS:
yield (klass, 'radial_gua-%.3f' % g,
factory(kernel=perceptron.radial_basis_gua_kernel(g),
**kwargs))
yield (klass, 'radial_mq-%.3f' % g,
factory(kernel=perceptron.radial_basis_mq_kernel(g),
**kwargs))
yield (klass, 'radial_thin-%.3f' % g,
factory(kernel=perceptron.radial_basis_thin_kernel(g),
**kwargs))
def learners():
kwargs = dict(event_size=EVENT_SIZE, outcome_size=OUTCOME_SIZE)
for klass in ('Perceptron', 'AveragedPerceptron'):
factory = getattr(perceptron, klass)
yield (klass, ' vanilla ', factory(**kwargs))
for d in DEGREES:
yield (klass,
'polynomial-%d' % d,
factory(kernel=perceptron.polynomial_kernel(d), **kwargs))
for g in GAMMAS:
yield (klass,
'radial_gua-%.3f' % g,
factory(kernel=perceptron.radial_basis_gua_kernel(g), **kwargs))
yield (klass,
'radial_mq-%.3f' % g,
factory(kernel=perceptron.radial_basis_mq_kernel(g), **kwargs))
yield (klass,
'radial_thin-%.3f' % g,
factory(kernel=perceptron.radial_basis_thin_kernel(g), **kwargs))
