SYMBOL INDEX (55 symbols across 11 files)

FILE: BSMan/ensemble.py
  function save_results (line 21) | def save_results(predictions, filename):

FILE: BSMan/logistic.py
  function group_data (line 24) | def group_data(data, degree=3, hash=hash):
  function OneHotEncoder (line 41) | def OneHotEncoder(data, keymap=None):
  function create_test_submission (line 69) | def create_test_submission(filename, prediction):
  function cv_loop (line 81) | def cv_loop(X, y, model, N):

FILE: classifier.py
  function main (line 34) | def main(CONFIG):

FILE: combine/combine.py
  function inverse_transform (line 18) | def inverse_transform(X):
  function print_param (line 24) | def print_param(obj, params, prefix=''):

FILE: external/ben.py
  function create_features (line 19) | def create_features():

FILE: external/greedy.py
  function group_data (line 22) | def group_data(data, degree=3, hash=hash):
  function OneHotEncoder (line 30) | def OneHotEncoder(data, keymap=None):
  function cv_loop (line 59) | def cv_loop(X, y, model, N):
  function create_features (line 73) | def create_features(train='data/train.csv', test='data/test.csv'):

FILE: helpers/data.py
  function load_data (line 16) | def load_data(filename, return_labels=True):
  function load_from_cache (line 30) | def load_from_cache(filename, use_cache=True):
  function save_results (line 44) | def save_results(predictions, filename):
  function save_dataset (line 53) | def save_dataset(filename, X, X_test, features=None, features_test=None):
  function get_dataset (line 71) | def get_dataset(feature_set='basic', train=None, cv=None):

FILE: helpers/diagnostics.py
  function plot_roc (line 12) | def plot_roc(fpr, tpr):
  function learning_curve (line 24) | def learning_curve(classifier, y, train, cv, n=15):

FILE: helpers/feature_extraction.py
  function sparsify (line 37) | def sparsify(X, X_test):
  function create_datasets (line 44) | def create_datasets(X, X_test, y, datasets=[], use_cache=True):
  function create_effects (line 164) | def create_effects(X_train, X_test, y):
  function create_features (line 198) | def create_features(X_train, X_test, feature_set=0):
  function pre_process (line 333) | def pre_process(features_train, features_test,
  function get_pivottable (line 402) | def get_pivottable(X_train, X_test, use='all'):
  function create_tuples (line 448) | def create_tuples(X):
  function create_triples (line 457) | def create_triples(X):
  function consolidate (line 467) | def consolidate(X_train, X_test):
  class OneHotEncoder (line 495) | class OneHotEncoder():
    method __init__ (line 500) | def __init__(self):
    method fit (line 503) | def fit(self, X):
    method transform (line 509) | def transform(self, X):

FILE: helpers/ml.py
  class AUCRegressor (line 77) | class AUCRegressor(object):
    method __init__ (line 78) | def __init__(self):
    method _auc_loss (line 81) | def _auc_loss(self, coef, X, y):
    method fit (line 85) | def fit(self, X, y):
    method predict (line 91) | def predict(self, X):
    method score (line 94) | def score(self, X, y):
  class MLR (line 99) | class MLR(object):
    method __init__ (line 100) | def __init__(self):
    method fit (line 103) | def fit(self, X, y):
    method predict (line 107) | def predict(self, X):
    method score (line 111) | def score(self, X, y):
  class StackedClassifier (line 116) | class StackedClassifier(object):
    method __init__ (line 138) | def __init__(self, models, generalizer=None, model_selection=True,
    method _combine_preds (line 149) | def _combine_preds(self, X_train, X_cv, y, train=None, predict=None,
    method _find_best_subset (line 176) | def _find_best_subset(self, y, predictions_list):
    method _get_model_preds (line 213) | def _get_model_preds(self, model, X_train, X_predict, y_train, cache_f...
    method _get_model_cv_preds (line 234) | def _get_model_cv_preds(self, model, X_train, y_train, cache_file):
    method fit_predict (line 262) | def fit_predict(self, y, train=None, predict=None, show_steps=True):
  function compute_subset_auc (line 344) | def compute_subset_auc(indices, pred_set, y):
  function find_params (line 352) | def find_params(model, feature_set, y, subsample=None, grid_search=False):

FILE: helpers/utils.py
  function stringify (line 11) | def stringify(model, feature_set):
  function compute_auc (line 19) | def compute_auc(y, y_pred):