·决策树学习Decision Tree Learning ·学习算法的实验评价Experimental Evaluation of Learning Algorithms ·规则学习：Rule Learning: Propositional and First Order ..
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学习算法的实验评价
Experimental evaluation of learning algorithms
以上为机器翻译结果，长、整句建议使用 人工翻译 。
实验结果表明：现有算法以16%的有效扩展规则覆盖了93%的标注正例，并使预期精度从51%提高到81%，显示了这套规则学习和评价方法的有效性。
Test results indicate that the algorithm can acquire about 16% of the useful expanded rules to cover 93% of the annotated positive examples and can improve the expected accuracy from 51% to 81%.
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