Neural Networks with R

Pros

The following are some of the advantages of neural networks:

• Neural networks are flexible and can be used for both regression and classification problems. Any data which can be made numeric can be used in the model, as neural network is a mathematical model with approximation functions.
• Neural networks are good to model with nonlinear data with large number of inputs; for example, images. It is reliable in an approach of tasks involving many features. It works by splitting the problem of classification into a layered network of simpler elements.
• Once trained, the predictions are pretty fast.
• Neural networks can be trained with any number of inputs and layers.
• Neural networks work best with more data points.