def launch():
DATA = read_data_sc2('../data/sequences-TZ-45.txt')[:5000]
DATA = reduce_k_length(10, DATA)
results = exhaustive(DATA, '1', top_k=10, enable_i=True)
print_results(results)
def launch():
# DATA = read_data_sc2('../data/sequences-TZ-45.txt')[:5000]
# DATA = read_data_kosarak('../data/skating.data')
# DATA = read_data(pathlib.Path(__file__).parent.parent / 'data/promoters.data')
DATA = read_jmlr('machin', pathlib.Path(__file__).parent.parent / 'data/jmlr/jmlr')
# DATA = read_data_kosarak('../data/figures_rc.dat')
target_class = '+'
results = misere(DATA, target_class, iterations_limit=50000, quality_measure='WRAcc')
print_results(results)
def launch():
# DATA = read_data_sc2('../data/sequences-TZ-45.txt')[:5000]
# DATA = read_data(pathlib.Path(__file__).parent.parent / 'data/promoters.data')
# DATA = read_jmlr('svm', pathlib.Path(__file__).parent.parent / 'data/jmlr/jmlr')
DATA = read_data('../data/splice.data')
# DATA = read_data_kosarak('../data/easy.data')
# DATA = read_data_kosarak('../data/skating.data')
# DATA, items_dict = read_retail('71270', pathlib.Path(__file__).parent.parent / 'data/retail.csv')
# print("Target item:{}".format(items_dict['71270']))
# DATA = read_data_kosarak('../data/figures_rc.dat')
# DATA = read_data_kosarak(pathlib.Path(__file__).parent.parent / 'data/context.data')
results = beam_search(DATA, 'EI', time_budget=100000000, enable_i=False, top_k=5, iterations_limit=10000,
beam_width=10, quality_measure='WRAcc')
print_results(results)
def launch():
# DATA = read_data_sc2('../data/sequences-TZ-45.txt')[:5000]
# DATA = reduce_k_length(10, DATA)
# DATA = read_data_kosarak('../data/skating.data')
# DATA = read_data_kosarak('../data/context.data')
# DATA = read_data(pathlib.Path(__file__).parent.parent / 'data/promoters.data')
DATA = read_jmlr('machin',
pathlib.Path(__file__).parent.parent / 'data/jmlr/jmlr')
# ITEMS = extract_items(DATA)
# ITEMS, items_to_encoding, encoding_to_items = encode_items(ITEMS)
# DATA = encode_data(DATA, items_to_encoding)
results = seq_scout(DATA,
'+',
time_budget=10,
top_k=5,
enable_i=False,
vertical=False,
iterations_limit=10000)
# results = seq_scout_api(DATA, '+', 10, 5)
print_results(results)
def display_info(stage, compute_count, sorted_patterns, begin, data, top_k):
print("The algorithm is at stage {} and did {}".format(stage, compute_count))
print("The algorithm took :{}".format(datetime.datetime.utcnow() - begin))
print("We print the best patterns")
patterns = sorted_patterns.get_top_k_non_redundant(data, top_k)
print_results(patterns)