What is feature interaction in machine learning?
The interaction between two features is the change in the prediction that occurs by varying the features after considering the individual feature effects. There is no interaction effect, because the model prediction is a sum of the single feature effects for size and location.
What are feature interactions?
Feature interaction is a software engineering concept. It occurs when the integration of two features would modify the behavior of one or both features. The term feature is used to denote a unit of functionality of a software application.
How do you know if its a main effect or interaction?
In statistics, main effect is the effect of one of just one of the independent variables on the dependent variable. There will always be the same number of main effects as independent variables. An interaction effect occurs if there is an interaction between the independent variables that affect the dependent variable.
How could I approach this problem with machine learning?
For example, it could be that the features a, f, and the interactions a:b:g, d:f and c:e are the 5 most important factors that predict the outcome. It is not only important for an algorithm to account for feature interactions, but I also want to be able to identify these interactions. How could I approach this problem with machine learning?
Why are there no interaction effects in machine learning?
There is no interaction effect, because the model prediction is a sum of the single feature effects for size and location. When you make a small house big, the prediction always increases by 100,000, regardless of location.
How to identify the features that are important for a machine learning?
This clearly indicates that RDSpend and MarketingSpend are the two features that are majorly important for generating a model that can predict the target feature. From both Statistical and Machine Learning methods, it is evident that RDSpend and MarketingSpend features are the ones that are required to determine the Profit of a startup company.
How can I generate a machine learning model?
From Model 3, the important features that required for generating a machine learning model, which can predict the target feature, are RDSpend and MarketingSpend. In this method, we create an actual machine learning model using one of the algorithms that output importance matrix as part of the model generation.