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Sales Forecasting using ARIMA

Hi everyone,

I'm still new to using RapidMiner and having problems when trying to deploy a sales forecast model using ARIMA. My data is a one-year sales transaction (60,000+ records).

Image: https://us.v-cdn.net/6030995/uploads/editor/z4/1zuh3fqj1o0g.png

Label: Tonnage
The purpose is to forecast tonnage but need to know the product group (Group_Name) column

For example, the forecast should be like this (assume - maybe need an additional column for more information)

Image: https://us.v-cdn.net/6030995/uploads/editor/jy/git43au5i1ai.png

I try to follow Dr. Fabian Temme's video about time series forecasting but still no luck.
Please help.

Best regards,
ScottBett

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rfuentealba

Hello, @ScottBett8

Sorry nobody has chimed in. Do you still have issues with ARIMA forecasting? I might be able to help.

All the best,

Rod.

Marco_Barradas

Hi @ScottBett8,

You could use a Group Into Collection and a Loop Collection operator for your use case.
It seems that you need to forecast the Qty on your problems since the Tonage is the result of Qty (variable a predictable) and Price (you may already have those prices or may need to predict ahead of time)

You'll need to install the operator toolbox extension to get access to the Group Into Collection operator.

I would also suggest you try the Forecasting Extension.
https://community.rapidminer.com/discussion/comment/66543#Comment_66543

If you want access to more time series training log into our free course
https://academy.rapidminer.com/learn/course/time-series-analytics/time-series-analytics/data-preparation-and-analysis

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ScottBett8

Hi @MarcoBarradas,

Sorry for the late reply. Got caught up in my work for weeks.
I tried your suggestion. It was a good idea to try your approach. Qty unit of measure is in Kg (kilograms) and Tonase is converted to Tons. After I apply your XML, indeed 14 product groups are generated. But the forecast is empty.

I also attach the XML

<?xml version="1.0" encoding="UTF-8"?><process version="9.9.002">

</context>

</operator>

</operator>

</list>

</operator>

</list>

</operator>

</operator>

</operator>

</operator>

</process>

</operator>

</process>

</operator>

</process>

I tried using the Forecast Validation operator but cannot run.

Regards,
ScottBett8

lionelderkrikor

Hi @ScottBett8,

Mmmh, it is expected that the first rows are not defined.
But can you confirm that the entire column "forecast of average (Tonase)" contains only interrogation marks ?
Moreover can you share your dataset in order we can run the process, see what is going on and fix it ?

Regards,

Lionel

ScottBett8

Hi @lionelderkrikor

Actually, not the entire column contains interrogation marks. Only part of it. But anyway, after searching and reading replies in the forum, I manage to complete the forecasting using Deep Learning and Random Forest model.

Just one last question if anybody can help or explain. When using the Windowing operator, the relative error is around 400%. Later, when not using the Windowing operator, the relative error is around <10%. I am still confused about the result.

Regards,

ScottBett