Neural netork models for time-series-predictor.
Project description
Time series models
Description
Time series neural network models for Time series predictor
Installation
pip install time-series-models
Usage example
from time_series_models import BenchmarkLSTM
from skorch.callbacks import EarlyStopping
from skorch.dataset import CVSplit
from torch.optim import Adam
from flights_time_series_dataset import FlightSeriesDataset
from time_series_predictor import TimeSeriesPredictor
tsp = TimeSeriesPredictor(
BenchmarkLSTM(),
lr = 1e-3,
lambda1=1e-8,
optimizer__weight_decay=1e-8,
iterator_train__shuffle=True,
early_stopping=EarlyStopping(patience=50),
max_epochs=250,
train_split=CVSplit(10),
optimizer=Adam
)
past_pattern_length = 24
future_pattern_length = 12
pattern_length = past_pattern_length + future_pattern_length
fsd = FlightSeriesDataset(pattern_length, past_pattern_length, pattern_length, stride=1)
tsp.fit(fsd)
mean_r2_score = tsp.score(tsp.dataset)
print(f"Achieved R2 score: {mean_r2_score}")
assert mean_r2_score > -20
Oze dataset history
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