Metadata-Version: 2.1
Name: gmlp
Version: 0.1a1
Summary: Genetic Algorithm for Python
Home-page: https://github.com/CoderWeird/gmlp
Author: Drew Montooth
Author-email: drewmontooth@gmail.com
License: UNKNOWN
Description: # 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 ->
        ```python
        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()
        ```
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.5
Requires-Python: >=2.5
Description-Content-Type: text/markdown
