# Prediction model **URL:** \ **Category:** KNIME Analytics Platform\ **Created:** [August 3, 2019, 12:59pm UTC](https://forum.knime.com/t/prediction-model/17331 "2019-08-03T12:59:42Z")\ **Posts on this page:** 1\ **Showing post:** 3
**Author:** ![mlauber71](https://forum-cdn.knime.com/user_avatar/forum.knime.com/mlauber71/32/73590_2.png) [@mlauber71](https://forum.knime.com/u/mlauber71)\ **Post date:** [August 4, 2019, 8:57am UTC](https://forum.knime.com/t/prediction-model/17331/3 "2019-08-04T08:57:06Z")
There is an example of the prediction of the number of customers to a restaurant using the powerful h2o.ai nodes of KNIME. Maybe you can adapt that: > **[Predict Demand Combining the Power of KNIME & H2O | KNIME](https://www.knime.com/blog/solving-a-kaggle-challenge-using-the-combined-power-of-knime-analytics-platform-h2o)** > > To tackle a Kaggle restaurant demand prediction challenge we decided to develop a cross-platform solution using the combined power of KNIME Analytics Platform and H2O. And also as @HansS mentioned there are lots of nodes and example around. Below are a few links about models for numeric targets that might be helpful. Also you might check out specific time series themes (I do not have a collection of links about that right now). > [@Predictive analytics for Sales](https://forum.knime.com/t/predictive-analytics-for-sales/12858/3): > > I can think of a few examples that might show you the possible directions This site has an introduction to model building with KNIME and uses an example that could be similar to your question: Concerning the predictions you want you will have to think about how to set up the analysis and prediction. Would you make a prediction for every single product and dealer and what role does the time play in your analysis. Sales within a month or a week. Then the quality of a model will very much de… > [@Forecasting sales per customer for the next 360 days](https://forum.knime.com/t/forecasting-sales-per-customer-for-the-next-360-days/13221/4): > > @ScottF provided us with simple workflow that shows how you would set up a regression model and do an evaluation using the RMSE ( Root-mean-square deviation) =\> the lower the better. The KNIME [numeric scorer node](https://nodepit.com/node/org.knime.base.node.mine.scorer.numeric.NumericScorerNodeFactory) has you covered there. You could switch out the type of model used: We had a discussion about that here: And also further information about ways to determine the quality of a model (mostly 1/0 but check out the link). I have to see if I have an example with a regression targe… > [@Evaluate a Linear Regression model](https://forum.knime.com/t/evaluate-a-linear-regression-model/13305/2): > > Typically you would use the Scorer nodes. Then there are a few entries dealing with numeric targets, you might want to check them. Regression models (numeric Target) predict how many future visitors a restaurant will receive (with H2O.ai) --- _[View the full topic](https://forum.knime.com/t/prediction-model/17331)._