Add to ORKGThe paper is concerned with the problem of binary classification of data records, given an already classified training set of records. Among the various approaches to the problem, the methodology of the logical analysis of data (LAD) is considered. Such approach is based on discrete mathematics, with special emphasis on Boolean functions. With respect to the standard LAD procedure, enhancements based on probability considerations are presented. In particular, the problem of the selection of the optimal support set is formulated as a weighted set covering problem. Testable statistical hypothesis are used. Accuracy of the modified LAD procedure is compared to that of the standard LAD procedure on datasets of the UCI repository. Encouraging re...
. The paper describes a new, logic-based methodology for analyzing observations. The key features of...
In this paper, we address the binary classification problem, in which one is given a set of observat...
In this paper we investigate logic classification and related feature selection algorithms for large...
The paper is concerned with the problem of binary classification of data records, given an already c...
This work deals with the problem of producing a fast and accurate binary classification of data reco...
Logical analysis of data (LAD), an approach to data analysis based on Boolean functions, combinatori...
Logical Analysis of Data (LAD) is a machine learning/data mining methodology that combines ideas fro...
About 20 years ago, we proposed an innovative approach to data mining based on a blend of Boolean te...
The Logical Analysis of Data (LAD) is a combinatorics, optimization and logic based methodology for ...
Initially introduced by Peter Hammer, Logical Analysis of Data is a methodology that aims at computi...
We consider data sets that consist of n-dimensional binary vectors representing positive and negativ...
Logical analysis of data (LAD) is a data analysis methodology used to solve the binary classificatio...
"Logical analysis of data" (LAD) is a methodology developed since the late eighties, aimed at discov...
We investigate an aspect of the construction of logical recognition algorithms - selection of patter...
We present a new process of analyzing data to determine critical at-tributes in a classification pro...
. The paper describes a new, logic-based methodology for analyzing observations. The key features of...
In this paper, we address the binary classification problem, in which one is given a set of observat...
In this paper we investigate logic classification and related feature selection algorithms for large...
The paper is concerned with the problem of binary classification of data records, given an already c...
This work deals with the problem of producing a fast and accurate binary classification of data reco...
Logical analysis of data (LAD), an approach to data analysis based on Boolean functions, combinatori...
Logical Analysis of Data (LAD) is a machine learning/data mining methodology that combines ideas fro...
About 20 years ago, we proposed an innovative approach to data mining based on a blend of Boolean te...
The Logical Analysis of Data (LAD) is a combinatorics, optimization and logic based methodology for ...
Initially introduced by Peter Hammer, Logical Analysis of Data is a methodology that aims at computi...
We consider data sets that consist of n-dimensional binary vectors representing positive and negativ...
Logical analysis of data (LAD) is a data analysis methodology used to solve the binary classificatio...
"Logical analysis of data" (LAD) is a methodology developed since the late eighties, aimed at discov...
We investigate an aspect of the construction of logical recognition algorithms - selection of patter...
We present a new process of analyzing data to determine critical at-tributes in a classification pro...
. The paper describes a new, logic-based methodology for analyzing observations. The key features of...
In this paper, we address the binary classification problem, in which one is given a set of observat...
In this paper we investigate logic classification and related feature selection algorithms for large...