The code is free, open source and available on Github so anyone can go and look to understand the implementation and functionality of genetic algorithm. It gives good optimisation and can even handle the noise in the input to a certain extent. Review collected by and hosted on G2.com.
One need to have knowledge of software language to use the algorithm. It will be difficult for a person without having programming background (like for a statistician) to implement it correctly and involves learning curve. Review collected by and hosted on G2.com.
The code is open in github and easy to implement. We can even handle error in input upto some extend. Review collected by and hosted on G2.com.
The parent child relationship and documentation can be improved further. Review collected by and hosted on G2.com.
Diversity feature has been used most effectively and very useful. Review collected by and hosted on G2.com.
The relationship between child and parent could be improved better. Review collected by and hosted on G2.com.
I like the ease of use of the genetic program. Its easy to use and teach people how to use as well. Review collected by and hosted on G2.com.
I dislike the layout of the program. I feel like there should be more prompts Review collected by and hosted on G2.com.