gmlp 0.1a2

Genetic Algorithm for Python

Genetic Machine Learning for Python

GMLP or Genetic Machine Learning for Python, is a user friendly python machine learning package. GMLP is intuitive and can be used for lots of Machine Learning Projects. An Example ->

from gmlp.evolution import Enviroment
from gmlp.mutations import value_encoding_mutation
from gmlp.fitness import Fitness_Function
import matplotlib.pyplot as plt
generations = 1000

hello = [0,1,1,0,1,0,0,0,0,1,1,0,0,1,0,1,0,1,1,0,1,1,0,0,0,1,1,0,1,1,0,0,0,1,1,0,1,1,1,1,0,0,1,0,0,0,0,0,0,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,0,0,1,0,0,1,1,0,1,1,0,0,0,1,1,0,0,1,0,0]
e = Enviroment(hello, .9)
population = e.generate_population(len(e.problem), binary=True)

scores = Fitness_Function().calculate_fitness(population, e.problem)
Outputs = []

best = min(scores)
best_ind = scores[scores.index(best)]

score_prog = []
score_prog.append(best_ind)
for generation in range(generations):
    scores = Fitness_Function().calculate_fitness(population, e.problem)
    best = min(scores)
    best_ind = scores[scores.index(best)]
    Output = population[scores.index(best)]

    score_prog.append(best_ind)
    Outputs.append(Output)
    print('Generation:%1d, Best Score:%1s, Output:%2s'%(generation, str(best_ind), str(Output)))
    population = value_encoding_mutation(e.crossover(e.tournament_selection(population, scores, 3), e.problem), .15)
    if min(scores) == 0:
        break
plt.plot(score_prog)
plt.xlabel("Generations")
plt.show()