- **General Discussion of Machine Learning**
(*http://book.caltech.edu/bookforum/forumdisplay.php?f=105*)

- - **Neural network with discrete and continuous input**
(*http://book.caltech.edu/bookforum/showthread.php?t=2691*)

Neural network with discrete and continuous inputDear Prof.
I have a question related to neural network. Can we train a neural network with inputs containing both discrete and continuous values? Does it affect on back-propagation algorithm? If it does, can we two separate network one for discrete inputs and one for continuous inputs? Thank you. |

Re: Neural network with discrete and continuous inputQuote:
For other types of discrete variables, there are still ways to code them for the network so that they can be used together with continuous variables. For instance, a variable that assumes 3 values that have no order can be coded as three binary variables, where only one of the variables is 1 and the others are 0 to designate one of the three values of the original variable. In all of these cases, it often helps to normalize the numerical range of the variables (say to mean 0 and variance 1) to avoid some of them dominating backpropagation by their shee numerical strength. |

All times are GMT -7. The time now is 11:35 PM. |

Powered by vBulletin® Version 3.8.3

Copyright ©2000 - 2020, Jelsoft Enterprises Ltd.

The contents of this forum are to be used ONLY by readers of the Learning From Data book by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin, and participants in the Learning From Data MOOC by Yaser S. Abu-Mostafa. No part of these contents is to be communicated or made accessible to ANY other person or entity.