Techniques for the logical analysis of binary data have successfully been applied to non-binary data which has been ‘binarized’ by means of cutpoints; see Boros et al. (1997, 2000) [7] and [8]. In this paper, we analyze the predictive performance of such techniques and, in particular, we derive generalization error bounds that depend on how ‘robust’ the cutpoints are
In this paper we propose a general framework to study the generalization properties of binary classi...
Floating-point computations are quickly finding their way in the design of safety- and mission-crit...
Abstract. We introduce a concrete semantics for floating-point operations which describes the propag...
Techniques for the logical analysis of binary data have successfully been applied to non-binary data...
AbstractTechniques for the logical analysis of binary data have successfully been applied to non-bin...
AbstractThis paper analyzes the predictive performance of standard techniques for the ‘logical analy...
This paper analyses the predictive performance of standard techniques for the `logical analysis of d...
We analyse the generalisation accuracy of standard techniques for the ‘logical analysis of data’, wi...
"Logical analysis of data" (LAD) is a methodology developed since the late eighties, aimed at discov...
We analyse the generalisation accuracy of standard techniques for the ‘logical analysis of data’, wi...
There is growing interest in devising non-statistical classification algorithms for multivariate pop...
An emerging area of research is to automatically compute reasonably accurate upper bounds on numeric...
This paper concerns learning binary-valued functions defined on, and investigates how a particular t...
AbstractThis paper concerns learning binary-valued functions defined on R, and investigates how a pa...
We present a new process of analyzing data to determine critical at-tributes in a classification pro...
In this paper we propose a general framework to study the generalization properties of binary classi...
Floating-point computations are quickly finding their way in the design of safety- and mission-crit...
Abstract. We introduce a concrete semantics for floating-point operations which describes the propag...
Techniques for the logical analysis of binary data have successfully been applied to non-binary data...
AbstractTechniques for the logical analysis of binary data have successfully been applied to non-bin...
AbstractThis paper analyzes the predictive performance of standard techniques for the ‘logical analy...
This paper analyses the predictive performance of standard techniques for the `logical analysis of d...
We analyse the generalisation accuracy of standard techniques for the ‘logical analysis of data’, wi...
"Logical analysis of data" (LAD) is a methodology developed since the late eighties, aimed at discov...
We analyse the generalisation accuracy of standard techniques for the ‘logical analysis of data’, wi...
There is growing interest in devising non-statistical classification algorithms for multivariate pop...
An emerging area of research is to automatically compute reasonably accurate upper bounds on numeric...
This paper concerns learning binary-valued functions defined on, and investigates how a particular t...
AbstractThis paper concerns learning binary-valued functions defined on R, and investigates how a pa...
We present a new process of analyzing data to determine critical at-tributes in a classification pro...
In this paper we propose a general framework to study the generalization properties of binary classi...
Floating-point computations are quickly finding their way in the design of safety- and mission-crit...
Abstract. We introduce a concrete semantics for floating-point operations which describes the propag...