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Hello,
I have a problem with time series analysis. I have a dataset with 5 features. Following is the subset of my input dataset:
date,price,year,day,totaltx
1/1/2016 0:00,434.46,2016,1,126762
1…
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#### Describe the bug
SARIMAX is great as it supports pandas series. However, it can be a bit "wrong" with seasonal series in real cases. That's because sometimes the seasonality is based on "time …
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* define the search space by model in `configs/configspace/..`
* depending of the model, get the right space and optimize with a generic optimize class
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**Question**
Hi,
First - thank you for developing this awesome package. I am using it for a while and find it very helpful.
I would like to constrain some coefficients to zero.
Is it possible …
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When I'm using latest version of scikit-hts package and trying to do a hierarchal forecasting that uses prophet model. Prophet version is 1.0 and pystan version is 2.19.1.1. When I'm trying to run
c…
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Hi I am trying som of statsmodels Time series models and noticed that for some of them there are no instructions on how to obtain out-of-sample forecasts. I am particularly interested in SARIMAX and D…
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Hi,
I use `FLAML==2.1.0`. I tried the timeseries forecasting tutorials which worked. When I use my own data I run into `KeyError`/`ValueError` issues when I try to `predict()` on the test data.
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tkeyo updated
10 months ago
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I am trying to train my own model on AWS Sagemaker in order to eventually create an endpoint, basically following this tutorial: https://github.com/aws/amazon-sagemaker-examples/tree/master/advanced_f…
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I have a fit SARIMAX model with 3 binary exogenous variables - in pseudocode:
```
df = pd.DataFrame(
data={
'endog': [...],
'exog_1': [...],
'exog_n: [...]
},
index=dates
)
…
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**Describe the bug**
When using `ColumnTransformer` in `ForecastingPipeline`,
- model.predict gives `ValueError: If passed as a pd.DataFrame, X must be a nested pd.DataFrame, with pd.Series or np.…