title: Why need to tune lambda with caret::train(..., method = "glmnet") and cv.glmnet()?
body: <p>As we can see that <code>caret::train(..., method = "glmnet")</code> with cross-validation or <code>cv.glmnet()</code> implemented both could find the <code>lambda.min</code> which minimize the cross-validation error. The final best fitted model should be the one fitted with <code>lambda.min</code>. Then, why do we need to set a grid of <code>lambda</code> values to the training process?</p>