Beispiel #1
0
    model_name = None
    models_names = [model_str for model_str in MODELS if model_str in arguments and arguments[model_str]]
    if models_names and len(models_names) == 1:
        model_name = models_names[0]

    if not model_name:
        print 'Please insert a valid model name'
        exit(0)
    ip_dir = arguments['--ip_dir']
    rating_file = os.path.join(ip_dir, EP_RATING)
    trust_file = os.path.join(ip_dir, EP_TRUST)
    uik = int(arguments['--uik'])
    uuk = int(arguments['--uuk'])
    generator = DataGen(rating_file, trust_file, uik=uik, uuk=uuk)
    generator.generate()
    print 'User Item Matrix Size:', generator.ui_matrix.shape
    print 'User User Matrix Size:', generator.uu_matrix.shape
    results = None
    threshold = None
    if model_name == 'mf':
        import matrixfac
        K = int(arguments['--K'])
        steps = int(arguments['--steps'])
        alpha = float(arguments['--alpha'])
        beta = float(arguments['--beta'])
        threshold = float(arguments['--threshold'])
        print 'Running MF with K=%d, steps=%d, threshold=%f, alpha=%f and beta=%f' % (K, steps, threshold, alpha, beta)
        results = matrixfac.run_rec(generator, k=K, steps=steps, alpha=alpha, beta=beta)

    print "RMSE: %f" % recstats.rmse(generator.ui_matrix, results)
    print "Coverage: %f " % recstats.coverage(results, threshold if threshold else 1)
Beispiel #2
0
    X = len(gen.ui_matrix[0])
    P = np.random.rand(N, k)
    Q = np.random.rand(M, k)

    R = uiu_matrix
    nP, nQ = matrix_factorization(R, P, Q, k, steps=steps, alpha=alpha, beta=beta)
    mf_results = np.dot(nP, nQ.T)
    # trimming off the trust part of the matrix
    mf_user_item_matrix = mf_results[0:W, 0:X]
    return mf_user_item_matrix


if __name__ == '__main__':
    import recstats
    # current file directory, keep the mat files in the same place
    ip_dir = os.getcwd()
    rating_file = os.path.join(ip_dir, EP_RATING)
    trust_file = os.path.join(ip_dir, EP_TRUST)

    generator = DataGen(rating_file, trust_file)
    ui_matrix = run_rec(generator, 100)
    
    print "RMSE: %f  Coverage: %f " % (recstats.rmse(generator.ui_matrix, ui_matrix), recstats.coverage(ui_matrix, 1))
    
    
    




Beispiel #3
0
        print 'Please insert a valid model name'
        exit(0)
    ip_dir = arguments['--ip_dir']
    rating_file = os.path.join(ip_dir, EP_RATING)
    trust_file = os.path.join(ip_dir, EP_TRUST)
    uik = int(arguments['--uik'])
    uuk = int(arguments['--uuk'])
    generator = DataGen(rating_file, trust_file, uik=uik, uuk=uuk)
    generator.generate()
    print 'User Item Matrix Size:', generator.ui_matrix.shape
    print 'User User Matrix Size:', generator.uu_matrix.shape
    results = None
    threshold = None
    if model_name == 'mf':
        import matrixfac
        K = int(arguments['--K'])
        steps = int(arguments['--steps'])
        alpha = float(arguments['--alpha'])
        beta = float(arguments['--beta'])
        threshold = float(arguments['--threshold'])
        print 'Running MF with K=%d, steps=%d, threshold=%f, alpha=%f and beta=%f' % (
            K, steps, threshold, alpha, beta)
        results = matrixfac.run_rec(generator,
                                    k=K,
                                    steps=steps,
                                    alpha=alpha,
                                    beta=beta)

    print "RMSE: %f" % recstats.rmse(generator.ui_matrix, results)
    print "Coverage: %f " % recstats.coverage(results,
                                              threshold if threshold else 1)