Full projects stored in .ipynb files
The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970. It is a zero-player game, meaning that its evolution is determined by its initial state, requiring no further input. One interacts with the Game of Life by creating an initial configuration and observing how it evolves. It is Turing complete and can simulate a universal constructor or any other Turing machine.
https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life
For each event occurance within a particle accelerator, many variables are measured.
Some events are not triggered by the desired collision and are in fact false positive measurements which need to be cut from the dataset. Data events can be cut above or below some value of an attribute. Choosing effective cuts disproportionately cuts false positives from the dataset. This algorithm makes the most effective cuts to remove unwanted datapoints.
Orange data is unwanted; after cutting, orange datapoints should be minimized.
Artificial neural networks can be used to classify events; here the scikitLearn library is used to classify a pseudo-random dataset.
