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Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

1 vote
1 answer
196 views

With two different random seeds for binary classification, I have the exact same result for ...

With a binary classification analysis, I find myself with the exact same accuracy, recall and specificity for both a qda and glm model. When I apply the same random seed to both classification model …
bolleke's user avatar
  • 77
1 vote
0 answers
604 views

Models have high accuracy but very low AUC PR curve

I'm doing balanced (70%-30%) binary classification (yes/no) I'm trying to combine caret train objects with PRROC's pr.curve function. I'm using a confusion matrix to determine which class is labelled …
bolleke's user avatar
  • 77
2 votes
0 answers
557 views

How to calculate variable importance for different models? is varImp() the solution?

I'm using caret's train() function for a binary classification outcome with different models (nb, knn, lda, qda, glm, rpart, rf). I'm using varImp() and plots to determine the importance of every fea …
bolleke's user avatar
  • 77
1 vote
1 answer
616 views

Importance value (with varImp from carret package) for one of the two numerical predictors h...

I'm using two numerical predictors to find an outcome, when using varImp (from the carret package) one of the predictors has 100 importance and the other 0. How should I interpret this?
bolleke's user avatar
  • 77