The ExponentialRegression class in the hana_ml.algorithms.pal.regression module is used to model the relationship between a scalar variable y and one or more variables denoted X using exponential functions, with parameters for matrix factorization type, adjusted R2 value inclusion, PMML model output, and thread ratio control.
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Here is a Python code template based on the provided help doc:

```python
from hana_ml.algorithms.pal.regression import ExponentialRegression

# Define the Exponential Regression model
er = ExponentialRegression(decomposition='QR', adjusted_r2=False, pmml_export='multi-row', thread_ratio=0.0)

# Assume df is the training data DataFrame
# df.collect()
# ID       Y       X1      X2
# 0   0     0.5     0.13    0.33
# 1   1    0.15     0.14    0.34
# 2   2    0.25     0.15    0.36
# 3   3    0.35     0.16    0.35
# 4   4    0.45     0.17    0.37

# Fit the model
er.fit(data=df, key='ID')

# Assume df2 is the data DataFrame for prediction
# df2.collect()
# ID    X1       X2
# 0   0   0.5      0.3
# 2   1     4      0.4
# 2   2     0      1.6
# 3   3   0.3     0.45
# 5   4   0.4      1.7

# Perform prediction
prediction = er.predict(data=df2, key='ID')

# Print the prediction result
print(prediction.collect())
# ID                      VALUE
# 0   0         0.6900598931338715
# 1   1         1.2341502316656843
# 2   2       0.006630664136180741
# 3   3         0.3887970208571841
# 4   4      0.0052106543571450266
```

Please replace `df` and `df2` with your actual data.