Auto_TS
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Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.
Prophet is now on version 1.0.1, in which it is called prophet instead of fbprophet. This updates that and allows it to run well with the updated package. Some verbiage...
model.fit not working I was using this library for thepast 4-5 days , every thing was working fine but now suddently getting an error in fitting the model model.fit(traindata=train, ts_column='Date',...
`ts_df[[target]]` here needs to be either a Series https://github.com/AutoViML/Auto_TS/blob/9fe2fcaae92209664deaf70b800865eb5e26ece1/auto_ts/__init__.py#L354 or this df needs to be converted to array in below block https://github.com/AutoViML/Auto_TS/blob/9fe2fcaae92209664deaf70b800865eb5e26ece1/auto_ts/utils/eda.py#L277-L293 as following throws error as it getting a...
Error with Augmented Dickey-Fuller test version used in this library. 'maxlag' is set to 31 and cannot be overridden. The same is updated in the statsmodels library. Please look at...
Would we be able to upgrade to the newer version of Prophet, that is now just called prophet? It seems like it would be an easy fix overall that I...
I don't know about the other models but one can use e.g. holiday regressors with Prophet. Can you use regressors with Auto_TS?
Break down the auto_ts unit tests into more modular unit tests. IT currently runs like regression tests and not unit tests * Break down [main flow unit tests](https://github.com/AutoViML/Auto_TS/blob/develop/auto_ts/test/test_auto_ts.py) into separate...
Predictions coming from ARIMA include extra information compared to SARIMAX and VAR. Need to make it consistent. https://github.com/AutoViML/Auto_TS/blob/develop/auto_ts/models/ar_based/arima.py#L191-L191 # ARIMA Models - [ ] Index value needs to be made...
https://github.com/AutoViML/Auto_TS/blob/196ad1fe9633a0935cc564884ff2247d7a2c8051/auto_ts/models/ar_based/var.py#L54-L54
# Prophet Model - [ ] predict function with simple=False returns 16 columns. See if this needs to be made consistent with the statistical models from statsmodels which return only...