Contents
How is caret used in predictive modeling and machine learning?
The process caret used was: Randomly sample the data with replacement. This means that a single observation could be chosen more than once. The total size of the modeling dataset will be the same as the original dataset but some sites will not be included and some will be included more than once.
Which is the most powerful feature of Caret?
As mentioned above, one of the most powerful aspects of the caret package is the consistent modeling syntax. By simply changing the method argument, you can easily cycle between, for example, running a linear model, a gradient boosting machine model and a LASSO model. In total, there are 233 different models available in caret.
How to retrieve overall accuracy value from confusionmatrix in R?
How to retrieve overall accuracy value from confusionMatrix in R? In R caret library, if I got a confusion matrix like this below, if there a way to retrieve the overall accuracy 0.992? I can’t get this single value out, since I need to store this value and use it for later processing.
How to get a realistic sense of predictive modeling?
To get a more realistic sense of how well you will predict a new dataset you can “pretend” some of your data is a new dataset and set that data aside. Then you can develop a model with the rest of the data then predict the unmodeled data and see how you did.
How to measure performance in the caret package?
7.0.20L2 Regularization 7.0.21Linear Classifier 7.0.22Linear Regression 7.0.23Logic Regression 7.0.24Logistic Regression 7.0.25Mixture Model 7.0.26Model Tree 7.0.27Multivariate Adaptive Regression Splines 7.0.28Neural Network 7.0.29Oblique Tree 7.0.30Ordinal Outcomes 7.0.31Partial Least Squares 7.0.32Patient Rule Induction Method
How is the train function used in caret?
The caret package has several functions that attempt to streamline the model building and evaluation process. The train function can be used to evaluate, using resampling, the effect of model tuning parameters on performance