Contents
What are the methods in the caret package?
7.0.31Partial Least Squares 7.0.32Patient Rule Induction Method 7.0.33Polynomial Model 7.0.34Prototype Models 7.0.35Quantile Regression 7.0.36Radial Basis Function 7.0.37Random Forest 7.0.38Regularization 7.0.39Relevance Vector Machines 7.0.40Ridge Regression 7.0.41Robust Methods 7.0.42Robust Model 7.0.43ROC Curves 7.0.44Rule-Based Model
When to use subsampling when using train in caret?
Recent versions of caret allow the user to specify subsampling when using train so that it is conducted inside of resampling. All four methods shown above can be accessed with the basic package using simple syntax.
Which is better subsample or estimate in caret?
The estimate is potentially better since the entire training set is being used but the subsample may happen to capture a small potion of the PCA space. There isn’t any obvious answer. The default behavior is to subsample the data prior to pre-processing. This can be easily changed and an example is given below.
How to randomly sample for class imbalances in caret?
For example, suppose that 80% of the training set samples are the first class and the remaining 20% are in the second class. Down-sampling would randomly sample the first class to be the same size as the second class (so that only 40% of the total training set is used to fit the model). caret contains a function ( downSample) to do this.
How to estimate model accuracy using the caret package?
It is a robust method for estimating accuracy, and the size of k and tune the amount of bias in the estimate, with popular values set to 3, 5, 7 and 10. The following example uses 10-fold cross validation to estimate Naive Bayes on the iris dataset.
What are the predictor variables in caret package?
The predictor variables are characteristics of the customer and the product itself. It contains 1070 rows with 18 columns. The response variable is ‘Purchase’ which takes either the value ‘CH’ (citrus hill) or ‘MM’ (minute maid).
How big is the dataset in caret package?
It contains 1070 rows with 18 columns. The response variable is ‘Purchase’ which takes either the value ‘CH’ (citrus hill) or ‘MM’ (minute maid). I have chosen a lightweight dataset so the focus is on getting familiar with the usage of caret package, instead of spending time on training models on large data.
How to select the best model in caret R?
After creating and tuning many model types, you may want know and select the best model so that you can use it to make predictions, perhaps in an operational environment. In this post you discover how to compare the results of multiple models using the caret R package.
How is the default data used in caret?
To illustrate caret, first for classification, we will use the Default data from the ISLR package. We first test-train split the data using createDataPartition. Here we are using 75% of the data for training. At first glance, it might appear as if the use of createDataPartition () is no different than our previous use of sample ().
What does the train function in caret return?
The train function in caret returns an S3 list object. On of the items in this list is called finalModel. This item is just the fitted object in it’s native form.