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Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full scientific model of the data, or merely represent local patterns in the data. Creating different algorithm and testing them with input data can be realized in the WEKA software. Additional tools are machine learning libraries for Python like scikit-learn.

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  • Rule induction (en)
  • 规则归纳 (zh)
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  • 规则归纳是机器学习的一个领域，是从观察集中将形式规则提取出来。提取的规则可能代表了全面的科学数据模型，或者只是代表了数据的本地模式。 (zh)
  • Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full scientific model of the data, or merely represent local patterns in the data. Creating different algorithm and testing them with input data can be realized in the WEKA software. Additional tools are machine learning libraries for Python like scikit-learn. (en)
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  • Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full scientific model of the data, or merely represent local patterns in the data. Data mining in general and rule induction in detail are trying to create algorithms without human programming but with analyzing existing data structures. In the easiest case, a rule is expressed with “if-then statements” and was created with the ID3 algorithm for decision tree learning. Rule learning algorithm are taking training data as input and creating rules by partitioning the table with cluster analysis. A possible alternative over the ID3 algorithm is genetic programming which evolves a program until it fits to the data. Creating different algorithm and testing them with input data can be realized in the WEKA software. Additional tools are machine learning libraries for Python like scikit-learn. (en)
  • 规则归纳是机器学习的一个领域，是从观察集中将形式规则提取出来。提取的规则可能代表了全面的科学数据模型，或者只是代表了数据的本地模式。 (zh)
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