The Croston class in the hana_ml.algorithms.pal.tsa.exponential_smoothing module is a forecasting strategy for products with intermittent demand, which uses separate exponential smoothing estimates of the average size of a demand and the average interval between demands to predict future demand.
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Here is a Python code template based on the provided help doc:

```python
from hana_ml.algorithms.pal.tsa.exponential_smoothing import Croston

# Create a Croston instance
croston = Croston(alpha=0.1,
                  forecast_num=1,
                  method='sporadic',
                  accuracy_measure='mape')

# Perform fit() on the given data
croston.fit_predict(data=df)

# Output
print(croston.forecast_.collect().set_index('ID').head(6))
print(croston.stats_.collect())
```

Please replace the data with your actual data and adjust the parameters of the `Croston` instance as needed.