Discovering genomes to use in machine learning techniques

A system, having a memory and a processor, for discovering machine learning genomes, the system comprising:

• a first component configured to generate a plurality of genomes, wherein each genome identifies at least one feature and at least one parameter for at least one machine learning algorithm, wherein generating a first genome of the plurality of genomes comprises:
• randomly selecting, from among a set of features, one or more of the features,
• randomly selecting, from among a set of parameters for at least one machine learning algorithm, one or more of the parameters, and
• assigning at least one random value to each of the selected parameters;
• a second component configured to, for each generated genome,
• train a one or more models using the generated genome, and
• for each model trained using the generated genome,
• calculate a fitness score for the trained model at least in part by applying the trained model to a validation data set, and
• produce a fitness score for the generated genome based at least in part on the fitness scores generated for the models trained using the generated genome;
• a third component configured to identify, from among the generated genomes, a plurality of genomes having a fitness score that exceeds a fitness threshold;
• and
• a fourth component configured to, for each of the identified genomes, mutate the identified genome,
• wherein at least one of the components comprises computer-executable instructions stored in the memory for execution by the system.