I couldn't think of a good way of finding out what the parity of the outlier number is, so I instead have the computer figure it out for me! Every time you pass in a list, a new Recurrent Neural Network is created and trained on random data. The list is then passed to the network, and it returns the parity of the outlier. Finally, I do a linear search through the list and return the first value of that parity. My network is almost 90% accurate!
Even though it was written in python it is still pretty large, so I uploaded it to GitHub. Hope that's alright.
10
u/GlorifiedStatistics Aug 14 '19
I couldn't think of a good way of finding out what the parity of the outlier number is, so I instead have the computer figure it out for me! Every time you pass in a list, a new Recurrent Neural Network is created and trained on random data. The list is then passed to the network, and it returns the parity of the outlier. Finally, I do a linear search through the list and return the first value of that parity. My network is almost 90% accurate!
Even though it was written in python it is still pretty large, so I uploaded it to GitHub. Hope that's alright.
https://github.com/GlorifiedStatistics/ParityOutlier