Add to ORKGIn this paper, it is shown how extracted patterns from data can be verified using decision tables (DTs). It is demonstrated how a complete and consistent decision table can be automatically modelled even if the extracted patterns contain anomalies. The proposed method is empirically validated on several benchmarking datasets. In addition to modelling a DT that is free of anomalies, it is shown that the DTs are sufficiently small such that the DTs can be consulted easil
We present an algorithm to verify the consistency and completeness of an object-oriented structured ...
The paper presents the presumably correct decision sets as a tool to analyze uncertainty in the form...
The data mining community is focused on a variety of methods and algorithms to manipulate incomplete...
On most datasets induction algorithms can generate very accurate classifiers. Sometimes, however, th...
On most datasets induction algorithms can generate very accurate classifiers. Sometimes, however, t...
On most datasets induction algorithms can generate very accurate classifiers. Sometimes, however, th...
Abstract. We evaluate the power of decision tables as a hypothesis space for supervised learning alg...
The use of decision tables to verify knowledge based systems (KBS) has been advocated several times ...
Companies' interest in customer relationship modelling and key issues such as customer lifetime valu...
Discusses eliminating contradictions among rules in computer-aided systems, experts rules, and datab...
The paper presents the presumably correct decision sets as a tool to analyze uncertainty in the form...
We present a mechanism for recovering consistent data from inconsistent set of assertions. For a com...
In this paper, the verification and validation of Knowledge-Based Systems (KBS) using decision table...
A number of Knowledge Graphs (KGs) on the Web of Data contain contradicting statements, and therefor...
In this paper, the verification and validation of Knowledge-Based Systems (KBS) using decision table...
We present an algorithm to verify the consistency and completeness of an object-oriented structured ...
The paper presents the presumably correct decision sets as a tool to analyze uncertainty in the form...
The data mining community is focused on a variety of methods and algorithms to manipulate incomplete...
On most datasets induction algorithms can generate very accurate classifiers. Sometimes, however, th...
On most datasets induction algorithms can generate very accurate classifiers. Sometimes, however, t...
On most datasets induction algorithms can generate very accurate classifiers. Sometimes, however, th...
Abstract. We evaluate the power of decision tables as a hypothesis space for supervised learning alg...
The use of decision tables to verify knowledge based systems (KBS) has been advocated several times ...
Companies' interest in customer relationship modelling and key issues such as customer lifetime valu...
Discusses eliminating contradictions among rules in computer-aided systems, experts rules, and datab...
The paper presents the presumably correct decision sets as a tool to analyze uncertainty in the form...
We present a mechanism for recovering consistent data from inconsistent set of assertions. For a com...
In this paper, the verification and validation of Knowledge-Based Systems (KBS) using decision table...
A number of Knowledge Graphs (KGs) on the Web of Data contain contradicting statements, and therefor...
In this paper, the verification and validation of Knowledge-Based Systems (KBS) using decision table...
We present an algorithm to verify the consistency and completeness of an object-oriented structured ...
The paper presents the presumably correct decision sets as a tool to analyze uncertainty in the form...
The data mining community is focused on a variety of methods and algorithms to manipulate incomplete...