Variables with Python Forecasting
Is there a way to use variables with a Python forecast model like ARIMA or Random Forest?
I have a linear regression working, and I'm able to extract the coefficients, create variables, and use a Beast Mode calculation to generate a forecast. However, I'm unsure if this can be done with models that aren’t linear.
Ideally, I'd like the user to input their exogenous/explanatory variables and see a forecast at the dashboard level. Has anyone done something similar?
Answers
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You should be able to use the Python tile to use Domo inputs or filtering. Run something like
from statsmodels.tsa.arima.model import ARIMA
y = your_time_series
X = your_exogenous_variable
model = ARIMA(y, exog=X, order=(p, d, q))
model_fit = model.fit()
forecast = model_fit.forecast(steps=10, exog=user_input_exog)** Was this post helpful? Click Agree or Like below. **
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Um…I did not put those numbers on that code. Hmm.
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I have a dataset and the model working right now, but the problem is getting input on the dashboard side of things.
If I create a webform I can create my own forecasts, but I'd like to be able to visualize that and incorporate variables so the user can see impact in real-time0
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