def main_with_validation(fileName, intercept=False, evalFunc = Util.brierScore):
trainX, trainY, testX, testY = Util.readData(fileName, intercept=intercept)
clf = GLS()
regs = np.logspace(-3, 3, 7)
xis = np.linspace(-1., 1.5, 26)
bestScore, bestXi, bestReg = 1e10, None, None
for xi in xis:
clf.setXi(xi)
print("Current xi = ", xi)
score, reg = Util.crossValidate(clf, trainX, trainY, \
evalFunc, 5, "Regular", regs)
if score < bestScore:
bestScore, bestXi, bestReg = score, xi, reg
print("bestScore, bestXi, bestReg = ", bestScore, bestXi, bestReg)
clf.setXi(bestXi)
clf.setRegular(bestReg)
clf.fit(trainX, trainY)
testScore = evalFunc(clf.predict(testX), testY)
with open("log/GLS_final_log.txt", 'a') as f:
log = ','.join([dt.now().strftime("%Y/%m/%d %H:%M"), str(fileName), \
str(bestReg), str(bestXi), str(intercept), \
evalFunc.__name__, str(bestScore), str(testScore)])
f.write(log + '\n')
