Add to ORKGAbstract. Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees – form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm) [6]
Since their early development, computers have had a profound impact on how we conduct modern scienti...
In this paper we are concerned with some general prop-erties of scientific hypotheses. We investigat...
This dissertation enhances data mining processes by formalizing them in a logic framework, with the ...
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledg...
This thesis describes a number of new data mining algorithms which were the result of our research i...
Advances of computational power, data collection and storage techniques are making new data availabl...
The objective of data mining is the extraction of knowledge from databases. In practice, one often e...
Statistically sound pattern discovery harnesses the rigour of statistical hypothesis testing to over...
textabstractThe monotonicity property is ubiquitous in our lives and it appears in different roles: ...
Abstract. We present a simple Data Mining Logic (DML) that can express common data mining tasks, lik...
Across many fields of social science, machine learning (ML) algorithms are rapidly advancing researc...
This monograph deals with mathematical constructions that are foundational in such an important area...
This paper describes a theory formation system which can discover a partial axiomization of a data b...
We propose the 'Seinhorst Research Program', derived from Seinhorst's empirical philosophy. All theo...
Unlocking the mystery of natural phenomena is a universal objective in scientific research. The rule...
Since their early development, computers have had a profound impact on how we conduct modern scienti...
In this paper we are concerned with some general prop-erties of scientific hypotheses. We investigat...
This dissertation enhances data mining processes by formalizing them in a logic framework, with the ...
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledg...
This thesis describes a number of new data mining algorithms which were the result of our research i...
Advances of computational power, data collection and storage techniques are making new data availabl...
The objective of data mining is the extraction of knowledge from databases. In practice, one often e...
Statistically sound pattern discovery harnesses the rigour of statistical hypothesis testing to over...
textabstractThe monotonicity property is ubiquitous in our lives and it appears in different roles: ...
Abstract. We present a simple Data Mining Logic (DML) that can express common data mining tasks, lik...
Across many fields of social science, machine learning (ML) algorithms are rapidly advancing researc...
This monograph deals with mathematical constructions that are foundational in such an important area...
This paper describes a theory formation system which can discover a partial axiomization of a data b...
We propose the 'Seinhorst Research Program', derived from Seinhorst's empirical philosophy. All theo...
Unlocking the mystery of natural phenomena is a universal objective in scientific research. The rule...
Since their early development, computers have had a profound impact on how we conduct modern scienti...
In this paper we are concerned with some general prop-erties of scientific hypotheses. We investigat...
This dissertation enhances data mining processes by formalizing them in a logic framework, with the ...