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Prescriptive Analytics
Newbie
Hello, I'm new to data analytics and rapidminer.
I'm working on a project where I want to see a family's income group will change or not after conducting a classification with new attributes such as monthly household expenditure and family size.
But I'm not sure what technique should I use for this.
All data is numeric and my class label(type of income group) is polynomial.
Anyone can help me?
I'm working on a project where I want to see a family's income group will change or not after conducting a classification with new attributes such as monthly household expenditure and family size.
But I'm not sure what technique should I use for this.
All data is numeric and my class label(type of income group) is polynomial.
Anyone can help me?
0
Answers
Welcome to the community.
You can use multiple classification models like tree-based (Decision tree, Random Forest and Gradient boosting) and libSVM in rapidminer. You can understand the performance of your models using a cross-validation method and select the best one with good performance.
On the other hand, you also have our effective auto model that provides you with reliable results quickly.
If you need to learn about building models in rapidminer, academy is a great place to start. https://academy.rapidminer.com/
If you have any specific needs, please inform us and we will provide more information.
Varun
https://www.varunmandalapu.com/
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