Predicting sales values using some past data (multiple features) by machine learning

Hello Community,
I have a dataset that containes those features : Year, Retailer country (country name), product type (string), Performence(float), sales (float $)
I have Year from 2004 to 2007 in this dataset
I want to use a machine learning algorithm in Knime so as to predict sales in 2008 for each couple (country,product type)

Any help thanks in advance

Hi @Abdessamad7

I think predicting sales or predicting whatever is absolutly possible with KNIME. Take a look at the KNIME Hub, and search for regression model workflow see the examples and get inspired. Or go to the KNIME learning hub. And also with KNIME comes the EXAMPLES server with lots of workflows dealing with predictive modelling.
gr. Hans

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Here we have a few examples for regression models with KNIME:

Regression models (numeric Target)

predict how many future visitors a restaurant will receive (with H2O.ai)

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