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

[tone_n_tune]

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.

[rfeigel]

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

[tone_n_tune]

@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.

[rfeigel]

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

xgboost regression hyperparameter optimization

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