Rule induction

Rule induction is an area of <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a> in which formal rules are extracted from a set of observations. The rules extracted may represent a full <a href="/facts/Scientific_model/aNyvIyUQ">scientific model</a> of the data, or merely represent local <a href="/facts/Patterns/mzD7uLQa">patterns</a> in the data.
<a href="/facts/Data_mining/AH53q5ac">Data mining</a> in general and rule induction in detail are trying to create algorithms without human programming but with analyzing existing data structures.: 415-  In the easiest case, a rule is expressed with “if-then statements” and was created with the <a href="/facts/ID3_algorithm/cey9VCT7">ID3 algorithm</a> for decision tree learning.: 7 : 348  Rule learning algorithm are taking training data as input and creating rules by partitioning the table with <a href="/facts/Cluster_analysis/HUeDnWPt">cluster analysis</a>.: 7  A possible alternative over the ID3 algorithm is genetic programming which evolves a program until it fits to the data.: 2 
Creating different algorithm and testing them with input data can be realized in the WEKA software.: 125  Additional tools are machine learning libraries for <a href="/facts/Python_/YbuGqofa">Python</a>, like <a href="/facts/Scikit-learn/HqxDHRMJ">scikit-learn</a>.

Rule induction open-in-new

Rule induction