Fix for typo in link

bookdown/04-Basic.Rmd

@@ -113,7 +113,7 @@ For a gradient boosting machine (GBM) model, there are three main tuning paramet
  - learning rate: how quickly the algorithm adapts, called `shrinkage`
  - the minimum number of training set samples in a node to commence splitting (`n.minobsinnode`)
 
-The default values tested for this model are shown in the first two columns (`shrinkage` and `n.minobsinnode` are not shown beause the grid set of candidate models all use a single value for these tuning parameters). The column labeled "`Accuracy`" is the overall agreement rate averaged over cross-validation iterations. The agreement standard deviation is also calculated from the cross-validation results. The column "`Kappa`" is Cohen's (unweighted) Kappa statistic averaged across the resampling results. `train` works with specific models (see [`train` Model List](available-models.html') or [`train` Models By Tag](train-models-by-tag.html)). For these models,  `train` can automatically create a grid of tuning parameters. By default, if *p* is the number of tuning parameters, the grid size is *3\^p*. As another example, regularized discriminant analysis (RDA) models have two parameters (`gamma` and `lambda`), both of which lie between zero and one. The default training grid would produce nine combinations in this two-dimensional space.
+The default values tested for this model are shown in the first two columns (`shrinkage` and `n.minobsinnode` are not shown beause the grid set of candidate models all use a single value for these tuning parameters). The column labeled "`Accuracy`" is the overall agreement rate averaged over cross-validation iterations. The agreement standard deviation is also calculated from the cross-validation results. The column "`Kappa`" is Cohen's (unweighted) Kappa statistic averaged across the resampling results. `train` works with specific models (see [`train` Model List](available-models.html) or [`train` Models By Tag](train-models-by-tag.html)). For these models,  `train` can automatically create a grid of tuning parameters. By default, if *p* is the number of tuning parameters, the grid size is *3\^p*. As another example, regularized discriminant analysis (RDA) models have two parameters (`gamma` and `lambda`), both of which lie between zero and one. The default training grid would produce nine combinations in this two-dimensional space.
 
 There is additional functionality in `train` that is described in the next section.