LazyProphet
Time Series Forecasting with LightGBM (by tblume1992)
ThymeBoost
Forecasting with Gradient Boosted Time Series Decomposition (by tblume1992)
| LazyProphet | ThymeBoost | |
|---|---|---|
| 2 | 2 | |
| 74 | 184 | |
| - | - | |
| 0.0 | 5.2 | |
| over 1 year ago | 10 months ago | |
| Python | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
LazyProphet
Posts with mentions or reviews of LazyProphet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-09.
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XGBoost for time series
If you want a quick thing to try for single time series you can try my package: LazyProphet which uses LightGBM under the hood.
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Best Python library for time series univariant stationary data prediction?[D]
If you are feeling adventurous you could try some of my packages: ThymeBoost or LazyProphet. ThymeBoost is interesting as it is gradient boosting around time series decomposition. So you will still have the trend/seasonality decomposition but with more exotic methods. LazyProphet is just some feature engineering for time series fed into Lightgbm but it tends to perform well enough. Both tend to outperform fbprophet although that generally isn't too hard to do and they both have automatic fitting procedure that performs ok.
ThymeBoost
Posts with mentions or reviews of ThymeBoost.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-03.
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Having trouble deseasonalising multiple parallel time series
As for Prophet itself, it generally gives you very smooth seasonality due to it's fitting procedure. I hate to always plug my stuff but you could try out ThymeBoost . Specifically passing seasonal_estimator='classic' (and I always like trend_estimator=['linear', 'ses']) as that would be a simple average of seasonal periods so it wouldn't be smoothed at all unless the periods aren't all spikey.
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Best Python library for time series univariant stationary data prediction?[D]
If you are feeling adventurous you could try some of my packages: ThymeBoost or LazyProphet. ThymeBoost is interesting as it is gradient boosting around time series decomposition. So you will still have the trend/seasonality decomposition but with more exotic methods. LazyProphet is just some feature engineering for time series fed into Lightgbm but it tends to perform well enough. Both tend to outperform fbprophet although that generally isn't too hard to do and they both have automatic fitting procedure that performs ok.
What are some alternatives?
When comparing LazyProphet and ThymeBoost you can also consider the following projects:
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
mlforecast - Scalable machine 🤖 learning for time series forecasting.