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())
