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.

How important is the confidence interval? Should I worry if the confidence is low?

Ras94Ras94 Member Posts: 3 Learner I
edited September 2019 in Help
Hi,

I have made two final models, both are performing equally good when cross validating. When it comes to deployment in a business setting, one of them shows very low confidence in its prediction (the most confident prediction is around .6 and even when its confidence is 0.25 or more, it decides to predict it as true.) How come? When it is predicting on the training and test set, it has much higher confidence in its predictions.

My other model is equally good in terms of cross validation, but when deploying it, it has much higher confidence in its prediction (most ranging from .6 to .9

Should I ignore this or can I conclude based on this, that the latter model is better to use?
Tagged:

Answers

  • IngoRMIngoRM Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,751 RM Founder
    Hi,
    Confidences in general are not comparable between different models.  They are calculated in different ways for each model type and you can not conclude that one model is better than another one just based on them (at least not without any additional postprocessing).  In general I would recommend to pick the model based on accuracy, scoring speed, understandability etc. and then adapt your business rules to the typical range of confidences produced by the selected model.
    Hope this helps,
    Ingo
Sign In or Register to comment.