# Credit
Idea from Boltzmann Brain by @pehringer.
# Installation & Usage
With Go installed, you can install the tool by running the following command:
1go get -u ysun.co/finch
To use as library, import the package:
1import "ysun.co/finch"
If you have a working Nix installation:
1nix run github.com/stepbrobd/finch
Source code: https://github.com/stepbrobd/finch
# Running Finch
Gates:
-input=2 -output=1 -hidden=2
2 input neurons, 1 output neuron, 1 hidden layer with 2 neurons
-population=128 -mutation=0.025
128 individules in the population, with 2.5% mutation rate
-example=./data/gates/input_data.csv -expected=./data/gates/{or,nor,xor}_label_data.csv
dataset paths
1finch -input=2 -output=1 -hidden=2 -population=128 -mutation=0.025 -example=./data/gates/input_data.csv -expected=./data/gates/{or,nor,xor}_label_data.csv
Remember to change which operation you want to run: OR, NOR, XOR.
Math:
-input=20 -output=19 -hidden=6,6,6,6
20 input neurons, 19 output neurons, 4 hidden layers with 6 neurons each
-population=32768 -mutation=0.01
32768 individules in the population, with 1% mutation rate
-example=./data/math/add_input_data.csv -expected=./data/math/add_output_data.csv
dataset paths
1finch -input=20 -output=19 -hidden=6,6,6,6 -population=32768 -mutation=0.01 -example=./data/math/add_input_data.csv -expected=./data/math/add_output_data.csv
MNIST:
-input=784 -output=10 -hidden=16,16
784 input neurons (28x28 greyscale images), 10 output neurons (numbers 1-10), 2 hidden layers with 16 neurons each
-population=4096 -mutation=0.1
4096 individules in the population, with 10% mutation rate
-example=./data/mnist/mnist_pixel_data_{32,64,128,256,512,1024,2048,4096,8192}.csv -expected=./data/mnist/mnist_label_data_{32,64,128,256,512,1024,2048,4096,8192}.csv
dataset paths
1finch -input=784 -output=10 -hidden=16,16 -population=4096 -mutation=0.1 -example=./data/mnist/mnist_pixel_data_{32,64,128,256,512,1024,2048,4096,8192}.csv -expected=./data/mnist/mnist_label_data_{32,64,128,256,512,1024,2048,4096,8192}.csv
Remember to change the size of MNIST dataset: 32, 64, 128, 256, 512, 1024, 2048, 4096, 8192.