Ila-2: an Inductive Learning Algorithm for Knowledge Discovery

In this paper we describe the ILA-2 rule induction algorithm, which is the improved version of a novel inductive learning algorithm ILA . We first outline the basic algorithm ILA, and then present how the algorithm is improved using a new evaluation metric that handles uncertainty in the data. By using a new soft computing metric, users can reflect their preferences through a penalty factor to control the performance of the algorithm. Inductive learning algorithm has also a faster pass criteria feature which reduces the processing time without sacrificing much from the accuracy that is not available in basic ILA. We experimentally show that the performance of ILA-2 is comparable to that of well-known inductive learning algorithms, namely, CN2, OC1, ID3, and C4.5.

[1]  Simon Kasif,et al.  A System for Induction of Oblique Decision Trees , 1994, J. Artif. Intell. Res..

[2]  Lotfi A. Zadeh,et al.  Soft computing and fuzzy logic , 1994, IEEE Software.

[3]  J. Rissanen.  Stochastic Complexity and Modeling , 1986 .

[4]  Usama M. Fayyad,et al.  Data Mining and Knowledge Discovery: Making Sense Out of Data , 1996, IEEE Expert.

[5]  Catherine Blake,et al.  UCI Repository of machine learning databases , 1998 .

[6]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[7]  Ron Kohavi,et al.  Data Mining Using MLC a Machine Learning Library in C++ , 1996, Int. J. Artif. Intell. Tools.

[8]  U. M. Feyyad.  Data mining and knowledge discovery: making sense out of data , 1996 .

[9]  Christopher J. Thornton,et al.  Techniques in computational learning - an introduction , 1992, Chapman and Hall Computing Series.

[10]  Evangelos Simoudis,et al.  Reality Check for Data Mining , 1996, IEEE Expert.

[11]  P. Heywood,et al.  Systems of Knowledge , 1987 .

[12]  Philip K. Chan,et al.  Systems for Knowledge Discovery in Databases , 1993, IEEE Trans. Knowl. Data Eng..

[13]  J. Ross Quinlan,et al.  Learning Efficient Classification Procedures and Their Application to Chess End Games , 1983 .

[14]  Saleh M. Abu-Soud,et al.  ILA: an inductive learning algorithm for rule extraction , 1998 .

[15]  Pat Langley,et al.  Elements of Machine Learning , 1995 .

[16]  Usama M. Fayyad,et al.  Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning , 1993, IJCAI.

[17]  Tsau Young Lin,et al.  Rough Sets and Data Mining: Analysis of Imprecise Data , 1996 .

[18]  Kai Ming Ting,et al.  Discretization of Continuous-Valued Attributes and Instance-Based Learning , 1994 .

[19]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .