https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Initialization-Procedure-vs-Preliminary-Training/m-p/654230#M875 <P>Re: Neural Network Modelling</P> <P>Which method is recommended between Initialization Procedure and Preliminary Training (page 3.5-3.6 of the course text)? Are there any instances where Preliminary Training may not be suitable?</P> Mon, 08 Jun 2020 07:04:30 GMT pvareschi 2020-06-08T07:04:30Z https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Initialization-Procedure-vs-Preliminary-Training/m-p/654230#M875 <P>Re: Neural Network Modelling</P> <P>Which method is recommended between Initialization Procedure and Preliminary Training (page 3.5-3.6 of the course text)? Are there any instances where Preliminary Training may not be suitable?</P> Mon, 08 Jun 2020 07:04:30 GMT https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Initialization-Procedure-vs-Preliminary-Training/m-p/654230#M875 pvareschi 2020-06-08T07:04:30Z https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Initialization-Procedure-vs-Preliminary-Training/m-p/695956#M977 <P>initialization is how every neural network initialize. SAS will do it at the back end for you so you just need to understand the method, no need to implement it and it is not an optional method/approach to choose.&nbsp;</P> <P>preliminary training is setting in proc neural, to allow neural network initialize multiple times and select the best. Sometimes the randomness in initialization would make you trap in local minimum, and you want to give your model several times to restart to avoid this.&nbsp;</P> <P>Always try the preliminary training approach. Often your data is too complicated for you to know if you trapped in a local minimum.&nbsp;</P> Mon, 02 Nov 2020 14:17:11 GMT https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Initialization-Procedure-vs-Preliminary-Training/m-p/695956#M977 zhongxiuliu 2020-11-02T14:17:11Z