predsc: Predictions from gbm and random forest on the Sonar test data
In MLeval: Machine Learning Model Evaluation

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The Sonar data was split into training (157 points) and testing (51 points), a gbm model was fitted using Caret on the training data. Then these are the predicted probabilities of the model on the test data. A random forest model was then fit and tested in the same manner. The probabilities and ground truth labels were combined horizontally for further analysis.