SYMBOL INDEX (121 symbols across 34 files)

FILE: compare_pu.py
  function init_args (line 20) | def init_args():
  function parse_args (line 51) | def parse_args(args):
  function force_ratio (line 64) | def force_ratio(params, x_data, y_data):
  function init_results (line 89) | def init_results(params):
  function add_result (line 100) | def add_result(results, params, percentage, pu_acc, b_clf_acc):
  function run_test (line 108) | def run_test(params, x_data, y_data):
  function main (line 175) | def main():

FILE: decorators.py
  function debug (line 5) | def debug(func):
  function print_step (line 19) | def print_step(func):

FILE: feature_engineering/length.py
  function create_length_feature (line 6) | def create_length_feature(params, input_vector, **kwargs):

FILE: feature_engineering/registry.py
  function register (line 8) | def register(name):
  function get_feature_extractor (line 19) | def get_feature_extractor(feature):

FILE: feature_engineering/tf.py
  function create_tf_vector (line 7) | def create_tf_vector(input_vector, tf_dict, vocabulary):
  function create_term_count_feature (line 21) | def create_term_count_feature(params, input_vector, **kwargs):

FILE: feature_engineering/tf_idf.py
  function create_tfidf_feature (line 12) | def create_tfidf_feature(params, train_vector, **kwargs):

FILE: feature_engineering/tf_ilf.py
  function create_tfilf_feature (line 12) | def create_tfilf_feature(params, train_vector, **kwargs):

FILE: feature_engineering/utils.py
  function load_feature_dict (line 9) | def load_feature_dict(params, name):
  function save_feature_dict (line 16) | def save_feature_dict(params, feat_dict, name):
  function binary_train_gtruth (line 22) | def binary_train_gtruth(y):
  function multi_features (line 26) | def multi_features(x, y):
  function get_features_vector (line 33) | def get_features_vector(log_vector, vocabulary, params):
  function extract_features (line 63) | def extract_features(x, params):

FILE: feature_engineering/vectorizer.py
  function get_ngrams (line 6) | def get_ngrams(n, line):
  function tokenize (line 25) | def tokenize(line):
  function build_vocabulary (line 30) | def build_vocabulary(inputData):
  function log_to_vector (line 52) | def log_to_vector(inputData, vocabulary):
  function setTrainDataForILF (line 79) | def setTrainDataForILF(x, y):
  function calculate_inv_freq (line 85) | def calculate_inv_freq(total, num):
  function get_max_line (line 89) | def get_max_line(inputVector):
  function get_tf (line 93) | def get_tf(inputVector):
  function get_lf (line 102) | def get_lf(inputVector):
  function calculate_idf (line 110) | def calculate_idf(token_index_dict, inputVector):
  function calculate_ilf (line 119) | def calculate_ilf(token_index_dict, inputVector):
  function create_invf_vector (line 129) | def create_invf_vector(inputVector, invf_dict, vocabulary):
  function normalize_tfinvf (line 144) | def normalize_tfinvf(tfinvf):
  function calculate_tf_invf_train (line 148) | def calculate_tf_invf_train(

FILE: init_params.py
  function init_main_args (line 8) | def init_main_args():
  function parse_main_args (line 159) | def parse_main_args(args):

FILE: logclass.py
  function init_args (line 24) | def init_args():
  function parse_args (line 31) | def parse_args(args):
  function inference (line 37) | def inference(params, x_data, y_data, target_names):
  function train (line 98) | def train(params, x_data, y_data, target_names):
  function main (line 179) | def main():

FILE: models/base_model.py
  class BaseModel (line 6) | class BaseModel(ABC):
    method __init__ (line 32) | def __init__(self, model, params):
    method save (line 40) | def save(self, **kwargs):
    method load (line 48) | def load(self, **kwargs):
    method predict (line 56) | def predict(self, X, **kwargs):
    method fit (line 69) | def fit(self, X, Y, **kwargs):

FILE: models/binary_registry.py
  function register (line 6) | def register(name):
  function get_binary_model (line 16) | def get_binary_model(model):

FILE: models/multi_registry.py
  function register (line 6) | def register(name):
  function get_multi_model (line 16) | def get_multi_model(model):

FILE: models/pu_learning.py
  class PUAdapterWrapper (line 9) | class PUAdapterWrapper(BaseModel):
    method __init__ (line 10) | def __init__(self, model, params):
    method save (line 13) | def save(self, **kwargs):
    method load (line 23) | def load(self, **kwargs):
  function instatiate_pu_adapter (line 38) | def instatiate_pu_adapter(params, **kwargs):

FILE: models/regular.py
  class RegularClassifierWrapper (line 8) | class RegularClassifierWrapper(BaseModel):
    method __init__ (line 9) | def __init__(self, model, params):
    method save (line 12) | def save(self, **kwargs):
    method load (line 20) | def load(self, **kwargs):
  function instatiate_regular_classifier (line 31) | def instatiate_regular_classifier(params, **kwargs):

FILE: models/svm.py
  class SVMWrapper (line 8) | class SVMWrapper(BaseModel):
    method __init__ (line 9) | def __init__(self, model, params):
    method save (line 12) | def save(self, **kwargs):
    method load (line 20) | def load(self, **kwargs):
  function instatiate_svm (line 31) | def instatiate_svm(params, **kwargs):

FILE: preprocess/bgl_preprocessor.py
  function process_line (line 12) | def process_line(line):
  function preprocess_dataset (line 37) | def preprocess_dataset(params):

FILE: preprocess/open_source_logs.py
  function process_line (line 10) | def process_line(line):
  function process_open_source (line 21) | def process_open_source(input_source, output):
  function preprocess_dataset (line 47) | def preprocess_dataset(params):

FILE: preprocess/registry.py
  function register (line 8) | def register(name):
  function get_preprocessor (line 18) | def get_preprocessor(data_src):

FILE: preprocess/utils.py
  function remove_parameters (line 16) | def remove_parameters(msg):
  function remove_parameters_slower (line 31) | def remove_parameters_slower(msg):
  function process_logs (line 48) | def process_logs(input_source, output, process_line=None):
  function load_logs (line 60) | def load_logs(params, ignore_unlabeled=False):

FILE: puLearning/puAdapter.py
  class PUAdapter (line 23) | class PUAdapter(object):
    method __init__ (line 33) | def __init__(self, estimator, hold_out_ratio=0.1, precomputed_kernel=F...
    method __str__ (line 56) | def __str__(self):
    method __fit_precomputed_kernel (line 61) | def __fit_precomputed_kernel(self, X, y):
    method __fit_no_precomputed_kernel (line 103) | def __fit_no_precomputed_kernel(self, X, y):
    method predict_proba (line 139) | def predict_proba(self, X):
    method predict (line 158) | def predict(self, X, treshold=0.5):

FILE: reporting/accuracy.py
  function model_accuracy (line 6) | def model_accuracy(y, pred):

FILE: reporting/bb_registry.py
  function register (line 6) | def register(name):
  function get_bb_report (line 16) | def get_bb_report(model):

FILE: reporting/confusion_matrix.py
  function report (line 6) | def report(y, pred):

FILE: reporting/macrof1.py
  function model_accuracy (line 6) | def model_accuracy(y, pred):

FILE: reporting/microf1.py
  function model_accuracy (line 6) | def model_accuracy(y, pred):

FILE: reporting/multi_class_acc.py
  function model_accuracy (line 6) | def model_accuracy(y, pred):

FILE: reporting/top_k_svm.py
  function get_feature_names (line 5) | def get_feature_names(params, vocabulary, add_length=True):
  function get_top_k_SVM_features (line 15) | def get_top_k_SVM_features(params, model, vocabulary, **kwargs):

FILE: reporting/wb_registry.py
  function register (line 6) | def register(name):
  function get_wb_report (line 16) | def get_wb_report(model):

FILE: run_binary.py
  function init_args (line 17) | def init_args():
  function parse_args (line 24) | def parse_args(args):
  function inference (line 31) | def inference(params, x_data, y_data, target_names):
  function main (line 61) | def main():

FILE: train_binary.py
  function init_args (line 20) | def init_args():
  function parse_args (line 27) | def parse_args(args):
  function train (line 34) | def train(params, x_data, y_data, target_names):
  function main (line 75) | def main():

FILE: train_multi.py
  function init_args (line 21) | def init_args():
  function parse_args (line 28) | def parse_args(args):
  function init_results (line 35) | def init_results():
  function add_result (line 47) | def add_result(results, params, macro, micro, train_time, run_time):
  function train (line 56) | def train(params, x_data, y_data, target_names):
  function main (line 105) | def main():

FILE: utils.py
  function trim (line 8) | def trim(s):
  class TestingParameters (line 13) | class TestingParameters():
    method __init__ (line 14) | def __init__(self, params):
    method __enter__ (line 18) | def __enter__(self):
    method __exit__ (line 21) | def __exit__(self, exc_type, exc_value, traceback):
  function load_params (line 25) | def load_params(params):
  function save_params (line 33) | def save_params(params):
  function file_handling (line 40) | def file_handling(params):
  function print_params (line 81) | def print_params(params):
  function save_results (line 90) | def save_results(results, params):