Python WorkUnit Beispiele

Beispiel #1

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn1', dnn1, 10000),
    ModelSpec('dnn2', dnn2, 10000),
    ModelSpec('dnn3', dnn3, 10000),
    ModelSpec('dnn6', dnn6, 10000),
]

# Work Units.

bitstamp_arb_rev_class = WorkUnit(
    'bitstamp_arb_rev_class',
    featuresets.bitstamp_arb_rev,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
        'handle_boundary': conversion.BOUNDARY_DROP,
    },
    model_specs=model_specs,
)

bitfinex_arb_rev_class = WorkUnit(
    'bitfinex_arb_rev_class',
    featuresets.bitfinex_arb_rev,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
        'handle_boundary': conversion.BOUNDARY_DROP,
    },
    model_specs=model_specs,
)

Beispiel #2

Datei: june_27_2017a.py Projekt: guanm326/atlas

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 1000),
    ModelSpec('dnn1', dnn1, 20000),
    ModelSpec('dnn2', dnn2, 20000),
    ModelSpec('dnn3', dnn3, 20000),
    ModelSpec('dnn6', dnn6, 20000),
]

# Work Units.
bitstamp_tails_oversample = WorkUnit(
    'bitstamp_tails_oversample',
    featuresets.ultra_strength_inner_1d_target_simple_returns_bitstamp,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.5, 0.95],
        'rebalance': True,
        'rebalance_method': 'oversample',
    },
    model_specs=model_specs,
)

# Bitfinex.
bitfinex_tails_oversample = WorkUnit(
    'bitfinex_tails_oversample',
    featuresets.ultra_strength_inner_1d_target_simple_returns_bitfinex,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.5, 0.95],
        'rebalance': True,
        'rebalance_method': 'oversample',

Beispiel #3

model_specs = [
    ModelSpec('linear', linear, 1000),
    ModelSpec('dnn1', dnn1, 20000),
    ModelSpec('dnn2', dnn2, 20000),
    ModelSpec('dnn3', dnn3, 20000),
    ModelSpec('dnn6', dnn6, 20000),
]


# Work Units.
bitstamp_deciles_oversample = WorkUnit(
    'bitstamp_deciles_oversample',
    featuresets.inner_1d_and_arb_bitstamp,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.10, 0.90],
        'rebalance': True,
        'rebalance_method': 'oversample',
    },
    model_specs=model_specs,
)

# Bitfinex.
bitfinex_deciles_oversample = WorkUnit(
    'bitfinex_deciles_oversample',
    featuresets.inner_1d_and_arb_bitfinex,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.10, 0.90],
        'rebalance': True,
        'rebalance_method': 'oversample',

Beispiel #4

model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn_small', dnn_small, 30000),
    ModelSpec('dnn_large', dnn_large, 30000),
    ModelSpec('dnn_dropout', dnn_dropout, 75000),
    ModelSpec('dnn_layers', dnn_layers, 75000),
]

# Work Units.
okcoin_price_diff_rebalanced_good_window = WorkUnit(
    'okcoin_price_diff_rebalanced_good_window',
    featuresets.ultra_strength_inner_1d_target_price_diff_okcoin,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
        'TRAIN_START': OKCOIN_TRAIN_START,
        'TRAIN_END': OKCOIN_TRAIN_END,
        'TEST_START': OKCOIN_TEST_START,
        'TEST_END': OKCOIN_TEST_END,
    },
    model_specs=model_specs,
)

gemini_price_diff_rebalanced_good_window = WorkUnit(
    'gemini_price_diff_rebalanced_good_window',
    featuresets.ultra_strength_inner_1d_target_price_diff_gemini,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
        'TRAIN_START': GEMINI_TRAIN_START,
        'TRAIN_END': GEMINI_TRAIN_END,

Beispiel #5

Datei: june_21_2017.py Projekt: guanm326/atlas

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 1000),
    ModelSpec('dnn1', dnn1, 10000),
    ModelSpec('dnn2', dnn2, 10000),
    ModelSpec('dnn3', dnn3, 10000),
    ModelSpec('dnn6', dnn6, 10000),
]

# Work Units.
bitstamp_deciles_oversample = WorkUnit(
    'bitstamp_deciles_oversample',
    featuresets.ultra_strength_inner_1d_target_simple_returns_bitstamp,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.10, 0.90],
        'rebalance': True,
        'rebalance_method': 'oversample',
    },
    model_specs=model_specs,
)

bitstamp_deciles_adasyn = WorkUnit(
    'bitstamp_deciles_adasyn',
    featuresets.ultra_strength_inner_1d_target_simple_returns_bitstamp,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.10, 0.90],
        'rebalance': True,
        'rebalance_method': 'adasyn'
    },

Beispiel #6

Datei: may_31_2017b.py Projekt: guanm326/atlas

regression_model_specs = [
    ModelSpec('linear', linear_reg, 100),
    ModelSpec('dnn1', dnn1_reg, 5000),
    ModelSpec('dnn2', dnn2_reg, 5000),
    ModelSpec('dnn3', dnn3_reg, 5000),
    ModelSpec('dnn6', dnn6_reg, 5000),
]

# Work Units.
bitstamp_arb_rev_class = WorkUnit(
    'bitstamp_arb_rev_class',
    featuresets.bitstamp_arb_rev,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
    },
    model_specs=classification_model_specs,
)

bitfinex_arb_rev_class = WorkUnit(
    'bitfinex_arb_rev_class',
    featuresets.bitfinex_arb_rev,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
    },
    model_specs=classification_model_specs,
)

Beispiel #7

Datei: may_31_2017.py Projekt: guanm326/atlas

regression_model_specs = [
    ModelSpec('linear', linear_reg, 100),
    ModelSpec('dnn1', dnn1_reg, 5000),
    ModelSpec('dnn2', dnn2_reg, 5000),
    ModelSpec('dnn3', dnn3_reg, 5000),
    ModelSpec('dnn6', dnn6_reg, 5000),
]

# Work Units.
bitstamp_arb_rev_class = WorkUnit(
    'bitstamp_arb_rev_class',
    featuresets.bitstamp_arb_rev,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
    },
    model_specs=classification_model_specs,
)

bitfinex_arb_rev_class = WorkUnit(
    'bitfinex_arb_rev_class',
    featuresets.bitfinex_arb_rev,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
    },
    model_specs=classification_model_specs,
)

Beispiel #8

Datei: new_spec_example.py Projekt: guanm326/atlas

# Model fn's.
def linear(td):
    return linc(td.shape[1], n_classes=2)


def dnn_small(td):
    return dnnc(td.shape[1], n_classes=2, hidden_layers=[td.shape[1]])


# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn_small', dnn_small, 1000),
]

# Work Units.
test_unit = WorkUnit(
    'test_unit',
    featuresets.simple_prices,
    featureset_params={},
    model_specs=model_specs,
)

# Work Spec.
pipeline_work_units = {
    0: [test_unit],
}

Spec = WorkSpec('test_spec', pipeline_work_units)

Beispiel #9

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn_small', dnn_small, 30000),
    ModelSpec('dnn_large', dnn_large, 30000),
    ModelSpec('dnn_dropout', dnn_dropout, 75000),
    ModelSpec('dnn_layers', dnn_layers, 75000),
]

# Work Units.
bitstamp_price_diff = WorkUnit(
    'bitstamp_price_diff',
    featuresets=featuresets.ultra_strength_inner_1d_target_price_diff_bitstamp,
    featureset_params={
        'for_classification': True,
    },
    model_specs=model_specs,
)

bitfinex_price_diff = WorkUnit(
    'bitfinex_price_diff',
    featuresets.ultra_strength_inner_1d_target_price_diff_bitfinex,
    featureset_params={
        'for_classification': True,
    },
    model_specs=model_specs,
)

coinbase_price_diff = WorkUnit(
    'coinbase_price_diff',

Beispiel #10

Datei: may_30_2017.py Projekt: guanm326/atlas

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn1', dnn1, 10000),
    ModelSpec('dnn2', dnn2, 10000),
    ModelSpec('dnn3', dnn3, 10000),
    ModelSpec('dnn6', dnn6, 10000),
]

# Work Units.
bitstamp_thirds_nobalance = WorkUnit(
    'bitstamp_thirds_nobalance',
    featuresets.ultra_strength_inner_1d_target_price_diff_bitstamp,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.33, 0.67],
        'rebalance': False,
    },
    model_specs=model_specs,
)

bitstamp_thirds_undersample = WorkUnit(
    'bitstamp_thirds_undersample',
    featuresets.ultra_strength_inner_1d_target_price_diff_bitstamp,
    featureset_params={
        'for_classification': True,
        'percentiles': [0.33, 0.67],
        'rebalance': True,
        'rebalance_method': 'undersample',
    },
    model_specs=model_specs,

Beispiel #11

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn1', dnn1, 20000),
    ModelSpec('dnn2', dnn2, 20000),
    ModelSpec('dnn3', dnn3, 20000),
    ModelSpec('dnn6', dnn6, 20000),
]


# Work Units.
bitstamp_reg = WorkUnit(
    'bitstamp_reg',
    featuresets.inner_1d_and_arb_bitstamp,
    featureset_params={
        'for_classification': False,
    },
    model_specs=model_specs,
)

# Bitfinex.
bitfinex_reg = WorkUnit(
    'bitfinex_reg',
    featuresets.inner_1d_and_arb_bitfinex,
    featureset_params={
        'for_classification': False,
    },
    model_specs=model_specs,
)

# Coinbase.

Beispiel #12

Datei: may_15_2017.py Projekt: guanm326/atlas

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn1', dnn1, 10000),
    ModelSpec('dnn2', dnn2, 10000),
    ModelSpec('dnn3', dnn3, 10000),
    ModelSpec('dnn6', dnn6, 10000),
]

# Work Units.
bitstamp_price_diff_rebalanced = WorkUnit(
    'bitstamp_price_diff_rebalanced',
    featuresets.ultra_strength_inner_1d_target_price_diff_bitstamp,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
    },
    model_specs=model_specs,
)

bitfinex_price_diff_rebalanced = WorkUnit(
    'bitfinex_price_diff_rebalanced',
    featuresets.ultra_strength_inner_1d_target_price_diff_bitfinex,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
    },
    model_specs=model_specs,
)

Beispiel #13

Datei: june_6_2017b.py Projekt: guanm326/atlas

# Model Specs.
model_specs = [
    ModelSpec('linear', linear, 100),
    ModelSpec('dnn1', dnn1, 5000),
    ModelSpec('dnn2', dnn2, 5000),
    ModelSpec('dnn3', dnn3, 5000),
    ModelSpec('dnn6', dnn6, 5000),
]


# Work Units.
bitstamp_price_diff_rebalanced = WorkUnit(
    'bitstamp_price_diff_rebalanced',
    featuresets.ultra_strength_inner_1d_target_price_diff_bitstamp,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
        'handle_boundary': conversion.BOUNDARY_DROP,
    },
    model_specs=model_specs,
)

bitfinex_price_diff_rebalanced = WorkUnit(
    'bitfinex_price_diff_rebalanced',
    featuresets.ultra_strength_inner_1d_target_price_diff_bitfinex,
    featureset_params={
        'for_classification': True,
        'rebalance': True,
        'handle_boundary': conversion.BOUNDARY_DROP,
    },
    model_specs=model_specs,
)