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Contribution of the predictors to the target variable, ROC curve Editing,
Please I have two questions:
1- How can I estimate the contribution of the predictors to the target variable in a binary classification problem.
2- How I can edit the figures exported from rapidminer and in particular ROC curve.
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Answers
If you are looking to understand the contribution if an attribute (predictor) on the prediction, RM has a "explain predictions operator", this operator will provide you with the predictors that supported and contradicted each prediction label (might be a correct or wrong prediction). This operator will calculate the local correlation of each predictor on the predicted label.
You can use online image editors for editing images or adobe tools.
Thanks
Varun
https://www.varunmandalapu.com/
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Lindon Ventures
Data Science Consulting from Certified RapidMiner Experts
100% agreement. In many cases it becomes "visually" obvious though since the globally important columns "stand out" since they have bolder colors in most cases. I saw that now quite often and I am thinking about putting this into an algorithm right now...
But you can also use any of the "Weighting" operators to calculate global importance BTW.
Just my 2 cents,
Ingo