def run(train, test, filename): log = Log(filename, 'n', train) log_bin = Log(filename.split('.log')[0] + '_bin.log', 'n', train) descriptSize = 4096 hidden_layer_sizes = 4096 / 4 inFeatsTrain, inLabelsTrain = getMatDescriptors(train, descriptSize) outFeatsTest, outLabelsTest = getMatDescriptors(test, descriptSize) print('Running with') limit = 9 * descriptSize + 1 while hidden_layer_sizes < limit: print('\tn: {}'.format(hidden_layer_sizes)) data = run_n(inFeatsTrain, inLabelsTrain, outFeatsTest, outLabelsTest, hidden_layer_sizes) log.add_data(data) log.log() data_bin = run_n_bin(inFeatsTrain, inLabelsTrain, outFeatsTest, outLabelsTest, hidden_layer_sizes) log_bin.add_data(data_bin) log_bin.log() hidden_layer_sizes += descriptSize / 4 # hidden_layer_sizes += 50 print('Finished running') print(log.max_data())
def run(train, test, filename): log = Log(filename, 'c', train) descriptSize = 4096 penalty = 0.5 inFeatsTrain, inLabelsTrain = getMatDescriptors(train, descriptSize) outFeatsTest, outLabelsTest = getMatDescriptors(test, descriptSize) print('Running with') while penalty < 10.5: print('\tc: {}'.format(penalty)) data = run_l(inFeatsTrain, inLabelsTrain, outFeatsTest, outLabelsTest, penalty) log.add_data(data) log.log() penalty += 0.5 print('Finished running') print(log.max_data())
def run(train, test, filename, k_i=1, k_f=101, inc=1): log = Log(filename, 'k', train) descriptSize = 4096 inFeatsTrain, inLabelsTrain = getMatDescriptors(train, descriptSize) outFeatsTest, outLabelsTest = getMatDescriptors(test, descriptSize) k = k_i print('Running with') while k < k_f: print('\tk: {}'.format(k)) data = run_k(inFeatsTrain, inLabelsTrain, outFeatsTest, outLabelsTest, k) log.add_data(data) log.log() k += inc print('Finished running') print(log.max_data())