# Example Workflows of Supervised Machine Learning on Time-series data?

**URL:** <https://forum.knime.com/t/example-workflows-of-supervised-machine-learning-on-time-series-data/78227>\
**Category:** KNIME Analytics Platform\
**Tags:** machine-learning, time-series\
**Created:** [March 30, 2024, 4:26pm UTC](https://forum.knime.com/t/example-workflows-of-supervised-machine-learning-on-time-series-data/78227 "2024-03-30T16:26:44Z")\
**Posts on this page:** 5\
**Page:** 1

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**Author:** ![tone\_n\_tune](https://forum-cdn.knime.com/letter_avatar_proxy/v4/letter/t/ebca7d/32.png) [@tone\_n\_tune](https://forum.knime.com/u/tone_n_tune)\
**Post date:** [March 30, 2024, 4:26pm UTC](https://forum.knime.com/t/example-workflows-of-supervised-machine-learning-on-time-series-data/78227/1 "2024-03-30T16:26:44Z")

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Hi All, I intend to use XGBoost on Time-series data. It appears that Time-series data needs to be made suitable for Supervised ML first by doing feature engineering. As such, I need some example workflows on Time-series data where XGBoost has been used.

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**Author:** ![rfeigel](https://forum-cdn.knime.com/letter_avatar_proxy/v4/letter/r/7ea924/32.png) [@rfeigel](https://forum.knime.com/u/rfeigel)\
**Post date:** [March 31, 2024, 3:21pm UTC](https://forum.knime.com/t/example-workflows-of-supervised-machine-learning-on-time-series-data/78227/2 "2024-03-31T15:21:14Z")

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This workflow doesn’t employ XGBoost, but does have a detailed discussion of data prep. It may help you.

> **[Time Series Analysis with KNIME — An introduction](https://medium.com/low-code-for-advanced-data-science/time-series-analysis-with-knime-an-introduction-7ce01a7ce055)**
>
> Learn the basic steps to perform no-code time series analysis with KNIME Analytics Platform and still leverage Python libraries

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**Author:** ![tone\_n\_tune](https://forum-cdn.knime.com/letter_avatar_proxy/v4/letter/t/ebca7d/32.png) [@tone\_n\_tune](https://forum.knime.com/u/tone_n_tune)\
**Post date:** [March 31, 2024, 3:31pm UTC](https://forum.knime.com/t/example-workflows-of-supervised-machine-learning-on-time-series-data/78227/3 "2024-03-31T15:31:22Z")

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> [@rfeigel](#):
>
> have a detailed discussion of data prep

Data prep for ML? Because the data needs to be treated differently for time-series analysis vs ML.

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**Author:** ![rfeigel](https://forum-cdn.knime.com/letter_avatar_proxy/v4/letter/r/7ea924/32.png) [@rfeigel](https://forum.knime.com/u/rfeigel)\
**Post date:** [April 1, 2024, 2:31am UTC](https://forum.knime.com/t/example-workflows-of-supervised-machine-learning-on-time-series-data/78227/4 "2024-04-01T02:31:49Z")

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Without knowing anything about your data or business case its hard offer specific suggestions. Look at this:

> [@xgboost regression hyperparameter optimization](https://forum.knime.com/t/xgboost-regression-hyperparameter-optimization/32823):
>
> hi dear form users ı m new to knime platform. ı have a quaestions. ı want to predict by using xgboost parameters={ "learning\_rate":[0.1,0.01,0.001], "n\_estimators":range(100, 1200, 100), } xgb\_model = xg.XGBRegressor(random\_state=0) this is my pyhton code and ı m searc by GridSearch to hyperparameter . how can ı do this on knime ?

> **[XGBoost For Time Series Forecasting: Don’t Use It Blindly](https://towardsdatascience.com/xgboost-for-time-series-forecasting-dont-use-it-blindly-9ac24dc5dfa9)**
>
> Forecasting techniques don’t work well with all time series

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**Author:** ![system](https://forum-cdn.knime.com/uploads/default/original/1X/ab3ccf34482a0329361734a18199390177204f15.png) [@system](https://forum.knime.com/u/system)\
**Post date:** [June 30, 2024, 2:32am UTC](https://forum.knime.com/t/example-workflows-of-supervised-machine-learning-on-time-series-data/78227/5 "2024-06-30T02:32:10Z")

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