def train_evaluate(ratios):
# model = CWSTrainer().train(msr_train, msr_train, msr_model, 0, 1, 8).getModel() # 训练模型
model = JClass('com.hankcs.hanlp.model.perceptron.model.LinearModel')(
msr_model)
pre = -1
scores = []
for c in ratios:
if c > 0:
print('以压缩比{}压缩模型中...'.format(c))
model.compress(1 - (1 - c) / pre, 0)
pre = 1 - c
result = CWSEvaluator.evaluate(
PerceptronLexicalAnalyzer(model).enableCustomDictionary(False),
msr_test, msr_output, msr_gold, msr_dict)
scores.append(result.F1)
return scores
