The aim of the article is to analyse and thoroughly research the methods of construction of the decision trees that use decision tree learning with statement propositionalized attributes. Classical decision tree learning algorithms, as well as decision tree learning with propositionalized attributes have been observed. The article provides the detailed analysis of one of the methodologies on the importance of using the decision trees in knowledge presentation. The concept of ontology use is offered to develop classification systems of decision trees. The application of the methodology would allow improving the classification accuracy
This study describes a model of explanations in natural language for classification decision trees. ...
This study describes a model of explanations in natural language for classification decision trees. ...
Decision tree learning is an important field of machine learning. In this study we examine both form...
The aim of the article is to analyse and thoroughly research the methods of construction of the deci...
The aim of the article is to analyse and develop an ontology-based classification system methodology...
Decision trees are one of the main methods for solving decision problems. The goal of this thesis is...
From its nature, decision-making processes and classi-fication tasks are domains, where decision tre...
The article presents sources of production knowledge and thoroughly describes its identification whi...
Abstract. Most learning algorithms for data-driven induction of pattern classifiers (e.g., the decis...
This paper discusses a basic design procedure for constructing decision trees from examples. We then...
Abstract. Decision tree learning represents a well known family of inductive learning algo-rithms th...
computer bookfair2015Includes bibliographical references and index.305 p.:Decision trees have become...
In medical decision making (classification, diagnosing, etc.) there are many situations where decisi...
There is a lot of approaches for data classification problems resolving. The most significant data c...
There is a lot of approaches for data classification problems resolving. The most significant data c...
This study describes a model of explanations in natural language for classification decision trees. ...
This study describes a model of explanations in natural language for classification decision trees. ...
Decision tree learning is an important field of machine learning. In this study we examine both form...
The aim of the article is to analyse and thoroughly research the methods of construction of the deci...
The aim of the article is to analyse and develop an ontology-based classification system methodology...
Decision trees are one of the main methods for solving decision problems. The goal of this thesis is...
From its nature, decision-making processes and classi-fication tasks are domains, where decision tre...
The article presents sources of production knowledge and thoroughly describes its identification whi...
Abstract. Most learning algorithms for data-driven induction of pattern classifiers (e.g., the decis...
This paper discusses a basic design procedure for constructing decision trees from examples. We then...
Abstract. Decision tree learning represents a well known family of inductive learning algo-rithms th...
computer bookfair2015Includes bibliographical references and index.305 p.:Decision trees have become...
In medical decision making (classification, diagnosing, etc.) there are many situations where decisi...
There is a lot of approaches for data classification problems resolving. The most significant data c...
There is a lot of approaches for data classification problems resolving. The most significant data c...
This study describes a model of explanations in natural language for classification decision trees. ...
This study describes a model of explanations in natural language for classification decision trees. ...
Decision tree learning is an important field of machine learning. In this study we examine both form...