Github user mktal commented on a diff in the pull request:
https://github.com/apache/incubator-madlib/pull/4#discussion_r45840119
--- Diff: src/ports/postgres/modules/svm/svm.py_in ---
@@ -440,55 +595,68 @@ def _process_epsilon(is_svc, args):
def _extract_params(schema_madlib, params, module='SVM'):
# NOTICE: the type of values in params_default should be consistent
with
# the types specified in params_types
- params_default = {'init_stepsize': 0.01,
- 'decay_factor': 0.9,
- 'max_iter': 100,
- 'tolerance': 1e-10,
- 'lambda': 1.0,
- 'norm': 'L2',
- 'n_folds': 0,
- 'epsilon': 0.01,
- 'eps_table': ''}
-
- params_types = {'init_stepsize': float,
- 'decay_factor': float,
- 'max_iter': int,
- 'tolerance': float,
- 'lambda': list,
- 'norm': str,
- 'n_folds': int,
- 'epsilon': float,
- 'eps_table': str}
+ params_default = {
--- End diff --
Early stopping in optimization serves the similar purposes as
regularizations do. Specifying those optimization parameters as lists allows
users to CV over them so that they are chosen to provide the `best`
generalization ability while avoiding over- or under-fitting. Another practical
concern is to make it easier for users to choose a proper init_stepsize which
varies from case to case depending on both the model and the data.
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