code to search linear combination weights

kktv_datagame_1711_linear_walker.py

# there are 32 weeks
weights_center = 0.5 * np.ones((32, 1))
weights_offset = np.zeros_like(weights_center)

auc_save = 0.8
auc_best = 0.0

for step in range(steps):
    # update weights
    weights = np.clip(weights_center + weights_offset, 0.0, 1.0)

    # weighted sum all features from training data (32 weeks x 28 slots)
    guess = np.matmul(train_eigens, weights).flatten()
    truth = train_labels

    # calculate the auc of weighted sum of all training data
    auc_test = auc(guess, truth)

    # keep the new weights if we got better AUC
    if auc_best < auc_test:
        auc_best = auc_test

        weights_center = weights

        print 'better auc: [{:>5}]: {:>10,.5f}'.format(step, auc_best)

        # save results
        if auc_save + 0.00001 <= auc_best:
            print 'saving'

            auc_save = auc_best

            # weighted sum of testing data
            guess = np.matmul(issue_eigens, weights_center)

            save_labels(guess)

    # pick new weights near the current best weights
    weights_offset = np.random.normal(np.zeros_like(weights_center), std)