def main():
#import bogota.data
options = DEFAULT_OPTIONS
print 'Getting Data'
#data = get_data(bogota.data.cn_all9, 0, normalise=50., seed=101)
data = GameData('./all9.csv', 50.)
train_data, test_data = data.train_test(0, seed=101)
perf, par = train(
options,
[train_data.datalist(), test_data.datalist()], False)
for k, v in par.iteritems():
print k
print v
def fold_function(k): # k is the fold index
data = GameData('./all9.csv', 50.)
train_data, test_data = data.train_test(k, seed=seed)
options['fold'] = k
llk, best_par = train(options,
[train_data.datalist(),
test_data.datalist()], False)
print "LLK: ", llk
for kk, vv in best_par.items():
temp = vv.tolist()
del best_par[kk]
best_par[kk] = temp
log_fold(best_loss_filename, llk, k, options.get('model_seed', -99))
with open(par_file % k, 'w') as f:
json.dump(best_par, f)
