Basic time – related machine learning models

Therefore, an amount of data with recent time periods needed to be selected as the validation set first and then other processes can be carried on like usual.

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Reference

Aishwarya S. (2019). 6 Powerful Feature Engineering Techniques For Time Series Data (using Python). Retrieved from https://www.analyticsvidhya.com/blog/2019/12/6-powerful-feature-engineering-techniques-time-series/

Bahnsen, A. C., Aouada, D., Stojanovic, A., & Ottersten, B. (2016). Feature engineering strategies for credit card fraud detection. Expert Systems with Applications51, 134-142.

Brown, R. G. (2004). Smoothing, forecasting and prediction of discrete time series. Courier Corporation.

Mishtert, T. (2019). Detecting Suspicious Timestamp In a Transfer or a Transaction Data. Retrieved from https://medium.com/@mishtert/detecting-suspicious-timestamp-analyzing-time-circular-histogram-e0b2e747e9bd

Stephanie G. (2019). Von Mises Distribution: Simple Definition & Examples. Retrieved from https://www.statisticshowto.com/von-mises-distribution/

Vegard F. (2019). How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls. Retrieved from https://www.kdnuggets.com/2019/05/machine-learning-time-series-forecasting.html

Vegard F. (2019). How (not) to use Machine Learning for time series forecasting: The sequel. Retrieved from https://www.kdnuggets.com/2020/03/machine-learning-time-series-forecasting-sequel.html#:~:text=Time%20series%20forecasting%20is%20an%20important%20area%20of%20machine%20learning.&text=However%2C%20while%20the%20time%20component,to%20many%20other%20prediction%20tasks

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