Due to recent updates, all users are required to create an Altair One account to login to the RapidMiner community. Click the Register button to create your account using the same email that you have previously used to login to the RapidMiner community. This will ensure that any previously created content will be synced to your Altair One account. Once you login, you will be asked to provide a username that identifies you to other Community users. Email us at Community with questions.

# NonLinear Forecast/Prediction

Member Posts: 3 Contributor I
edited November 2018 in Help
Hej guys,

I HAVE A QUESTION  ::)
I`m currently working on a pricing-issue where I want to forecast the price-decrease of several products.

THE PROBLEM: The historical data points out that the price decreased non-linear so far. Instead it decreases quite strong at the beginning but the longer the product is on the market the more the price approaches a zero decline. I`m pretty much a beginner with Rapidminer and could only figure out that linear regression would not help me to forecast scoring-datasets in a meaningful manner.

WHAT TO DO?
Can you help me with that?

br

• Member Posts: 3 Contributor I
I would be happy for any small hints to get started because running through several Youtube Videos and the Manual didnt help so far.
Probably I also explained the problem not got enough.

The price decreases over time as follows (just an example):

01.01.2012 - 350€
01.03.2012 - 300€
01.06.2012 - 270€
01.09.2012 - 245€
01.12.2012 - 227€
01.03.2013 - 215€
01.06.2013 - 205€
01.09.2013 - 197€
01.12.2013 - 191€

What I need to do is a prediction for the upcoming months. It seems like a logarithmic trend but I dont know how to build such a process effectively.
• RapidMiner Certified Expert, Member Posts: 1,869 Unicorn
Hi,

if you know that the descent is logarithmic you can try to transform the data before applying a Linear Regression with the Generate Attributes operator, e.g. by taking exp(price).
In the general case you can use one of the various non-linear regression algorithms like SVM with radial kernel or Gaussian Process.

Best regards,
Marius
• Member Posts: 3 Contributor I
Hej Marius,

BIG THANKS for your response. I haven´t expected anyone answering anymore and unfortunately I didnt get any message that I fortunately got a response. Anyways, I tried the SVM as well as Neural Networks and it works good for my purpose. I would like to understand your advice to use the exp(price) function for applying linear regression. It seems that it almost straightens the price function except for the first point (300€) but how do I proceed from their? How should I transform the testing/scoring set to apply the regression and get a reasonable forecast?

Furthermore I was wondering how I can arrange the algorithm to measure seperate values according to the ID. I have product A, product B and product C in my dataset and each has different prices and accordingly different price curves. I indicate the product name as ID but when I run the SVM it can´t distinguish between the different products and gives just a mutual value for each product as if they were al the same. What am I doing wrong in this case?

Cheers