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Better 'Gradientenabstieg'

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This commit is contained in:
Dominik Moritz Roth 2021-11-23 20:51:24 +01:00
parent 5f7366e556
commit ef7fceacea
2 changed files with 5 additions and 5 deletions
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8
caliGraph.py
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@ -841,7 +841,7 @@ def evaluateFitness(books, debugPrint=False):
fit = sum(errSq)/len(errSq) + 0.005*regressionLoss + 0.2*boundsLoss/len(ratedBooks) - 1.0*sum(linSepLoss)/len(linSepLoss)
return fit, gradient
def train(initGamma = 1, full=True):
def train(initGamma, full=True):
global weights
if full:
for wt in weights:
@ -854,12 +854,12 @@ def train(initGamma = 1, full=True):
best_mse = mse
stagLen = 0
while gamma > 3.0e-06 and delta > 3.0e-05 or best_mse > 3:
while gamma > 3.0e-05 and delta > 3.0e-05 or best_mse > 3:
last_mse = mse
print({'mse': mse, 'gamma': gamma, 'delta': delta})
delta = sum(gradient[g]**2 for g in gradient)
for wt in weights:
weights[wt] += gamma*gradient[wt]
weights[wt] += gamma*gradient[wt]/math.sqrt(delta)
mse, gradient = evaluateFitness(books)
if mse < last_mse:
gamma = gamma*1.25
@ -932,7 +932,7 @@ def cliInterface():
p_show.add_argument('-d', type=float, default=2.7, help='depth of expansion')
p_train = cmds.add_parser('train', description="TODO", aliases=[])
p_train.add_argument('-g', type=float, default=1, help='learning rate gamma')
p_train.add_argument('-g', type=float, default=0.1, help='learning rate gamma')
p_train.add_argument('--full', action="store_true")
p_full = cmds.add_parser('full', description="TODO", aliases=[])

2
neuralWeights.json
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@ -1 +1 @@
{"topList": 0.7565347246764587, "recommender": 0.6271368623961752, "author": 1.835086355564805, "series": 0.05208524913006312, "tag": 0.0035089366917880893, "mu": 0.6199999161572797, "sigma": 0.0711803151840928, "se": 0.5310718593481506, "bias": 0.5726915883403473}
{"topList": 0.46904994817058576, "recommender": 0.5105580165380674, "author": 1.2017599208712688, "series": 0.08101540889409455, "tag": 0.01759005368430446, "mu": 0.6921620983533125, "sigma": 0.016831028550919676, "se": 0.3363180764359938, "bias": 0.15960517748561318}