def main():
run_single_experiment(MethodMarkov, {'reg_factor': REGULARIZATION_FACTOR},
UIData, {'num_test': NUM_TEST_SAMPLES}, 2,
FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodBBCF, {
'reg_factor': REGULARIZATION_FACTOR,
'num_models': NUM_TASKS
}, UIData, {'num_test': NUM_TEST_SAMPLES}, 2, FIXED_LENGTHS, 10, fsuffix,
RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'euclidean',
'stride': 1
}, UIData, {'num_test': NUM_TEST_SAMPLES}, 2, FIXED_LENGTHS, 10, fsuffix,
RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'cosine',
'stride': 1
}, UIData, {'num_test': NUM_TEST_SAMPLES}, 2, FIXED_LENGTHS, 10, fsuffix,
RND_SEED, show_result)
run_single_experiment(
MethodLSTM, {
'max_seq_len': 30,
'strat': 'sequential',
'epochs': 20,
'fname': 'lstm_model'
}, UIData, {'num_test': NUM_TEST_SAMPLES}, 2, FIXED_LENGTHS, 10,
fsuffix, RND_SEED, show_result)
def main():
run_single_experiment(MethodMarkov, {'reg_factor': REGULARIZATION_FACTOR},
SyntheticData, {
'num_samples': NUM_TRAINING_SAMPLES,
'seplvl': TASK_SEP,
'seed': RND_SEED
}, 2, FIXED_LENGTHS, NUM_FOLDS, fsuffix, RND_SEED,
show_result)
run_single_experiment(MethodBBCF, {
'reg_factor': REGULARIZATION_FACTOR,
'num_models': NUM_TASKS
}, SyntheticData, {
'num_samples': NUM_TRAINING_SAMPLES,
'seplvl': TASK_SEP,
'seed': RND_SEED
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'euclidean',
'stride': 3
}, SyntheticData, {
'num_samples': NUM_TRAINING_SAMPLES,
'seplvl': TASK_SEP,
'seed': RND_SEED
}, 2, FIXED_LENGTHS, NUM_FOLDS, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'cosine',
'stride': 3
}, SyntheticData, {
'num_samples': NUM_TRAINING_SAMPLES,
'seplvl': TASK_SEP,
'seed': RND_SEED
}, 2, FIXED_LENGTHS, NUM_FOLDS, fsuffix, RND_SEED, show_result)
run_single_experiment(
MethodLSTM, {
'max_seq_len': 20,
'strat': 'sequential',
'epochs': 20,
'fname': 'lstm_model'
}, SyntheticData, {
'num_samples': NUM_TRAINING_SAMPLES,
'seplvl': TASK_SEP,
'seed': RND_SEED
}, 2, FIXED_LENGTHS, NUM_FOLDS, fsuffix, RND_SEED, show_result)
def main():
run_single_experiment(MethodMarkov, {'reg_factor': REGULARIZATION_FACTOR},
TaxiData, {
'num_samples': TRAIN_SIZE,
'grid': GRID_SIZE
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED,
show_result)
run_single_experiment(MethodBBCF, {
'reg_factor': REGULARIZATION_FACTOR,
'num_models': NUM_GOALS
}, TaxiData, {
'num_samples': TRAIN_SIZE,
'grid': GRID_SIZE
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'euclidean',
'stride': 5
}, TaxiData, {
'num_samples': TRAIN_SIZE,
'grid': GRID_SIZE
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'cosine',
'stride': 5
}, TaxiData, {
'num_samples': TRAIN_SIZE,
'grid': GRID_SIZE
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(
MethodLSTM, {
'max_seq_len': 10,
'strat': 'sequential',
'epochs': 20,
'fname': 'lstm_model'
}, TaxiData, {
'num_samples': TRAIN_SIZE,
'grid': GRID_SIZE
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
def main():
run_single_experiment(MethodNN, {
'distfcn': 'euclidean',
'stride': STRIDE[SKILL_SET]
}, KTData, {
'skill_set': SKILL_SET,
'merge': True
}, 1, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'cosine',
'stride': STRIDE[SKILL_SET]
}, KTData, {
'skill_set': SKILL_SET,
'merge': True
}, 1, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(
MethodLSTM, {
'max_seq_len': 10,
'strat': 'sequential',
'epochs': 20,
'fname': 'lstm_model'
}, KTData, {
'skill_set': SKILL_SET,
'merge': True
}, 1, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
def main():
print('{:s}\nNumber of training samples {:d}\n{:s}'.format(
''.join(40 * ['-']), TRAIN_SIZE, ''.join(40 * ['-'])))
run_single_experiment(MethodMarkov, {'reg_factor': REGULARIZATION_FACTOR},
SparseTaxiData, {
'num_samples': LOAD_SIZE,
'num_train': TRAIN_SIZE,
'num_test': TEST_SIZE,
'num_goals': NUM_GOALS,
'grid': [20, 20]
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED,
show_result)
# number of destinations is limited
run_single_experiment(MethodBBCF, {
'reg_factor': REGULARIZATION_FACTOR,
'num_models': NUM_GOALS
}, SparseTaxiData, {
'num_samples': LOAD_SIZE,
'num_train': TRAIN_SIZE,
'num_test': TEST_SIZE,
'num_goals': NUM_GOALS,
'grid': [20, 20]
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'euclidean',
'stride': 3
}, SparseTaxiData, {
'num_samples': LOAD_SIZE,
'num_train': TRAIN_SIZE,
'num_test': TEST_SIZE,
'num_goals': NUM_GOALS,
'grid': [20, 20]
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)
run_single_experiment(MethodNN, {
'distfcn': 'cosine',
'stride': 3
}, SparseTaxiData, {
'num_samples': LOAD_SIZE,
'num_train': TRAIN_SIZE,
'num_test': TEST_SIZE,
'num_goals': NUM_GOALS,
'grid': [20, 20]
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED)
run_single_experiment(
MethodLSTM, {
'max_seq_len': 10,
'strat': 'sequential',
'epochs': 20,
'fname': 'lstm_model'
}, SparseTaxiData, {
'num_samples': LOAD_SIZE,
'num_train': TRAIN_SIZE,
'num_test': TEST_SIZE,
'num_goals': NUM_GOALS,
'grid': [20, 20]
}, 2, FIXED_LENGTHS, 10, fsuffix, RND_SEED, show_result)