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Tweaked training

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Dominik Moritz Roth 2021-09-24 16:32:43 +02:00
parent cf85995386
commit fb3a5592df
1 changed files with 12 additions and 3 deletions
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11
caliGraph.py
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@ -682,6 +682,9 @@ def evaluateFitness():
rating = G.nodes[m]['rating'] rating = G.nodes[m]['rating']
G.nodes[m]['rating'] = None G.nodes[m]['rating'] = None
mu, std = genScores(G, books) mu, std = genScores(G, books)
if G.nodes[m]['score'] > rating: # over estimated
errSq.append(((rating - G.nodes[m]['score'])**2)*1.5)
else:
errSq.append((rating - G.nodes[m]['score'])**2) errSq.append((rating - G.nodes[m]['score'])**2)
G.nodes[m]['rating'] = rating G.nodes[m]['rating'] = rating
return sum(errSq) / len(errSq) return sum(errSq) / len(errSq)
@ -697,11 +700,17 @@ def train(gamma = 0.1):
while True: while True:
print({'mse': best_mse, 'w': weights, 'gamma': gamma}) print({'mse': best_mse, 'w': weights, 'gamma': gamma})
weights = copy.copy(bestWeights) weights = copy.copy(bestWeights)
if gamma < 0.01 and random.random() < 0.5:
gamma = 0.01
weights[attr] = -1+random.random()*2
else:
weights[attr] += delta weights[attr] += delta
if attr not in ['sigma, mu']:
weights[attr] = min(max(0, weight[attr]), 1.5)
mse = evaluateFitness() mse = evaluateFitness()
if mse < best_mse: # got better if mse < best_mse: # got better
saveWeights(weights) saveWeights(weights)
gamma *= 1.1 gamma *= 1.75
bestWeights = copy.copy(weights) bestWeights = copy.copy(weights)
best_mse = mse best_mse = mse
delta *= 2 delta *= 2