This study describes a model of explanations in natural language for classification decision trees. The explanations include global aspects of the classifier and local aspects of the classification of a particular instance. The proposal is implemented in the ExpliClas open source Web service [1], which in its current version operates on trees built with Weka and data sets with numerical attributes. The feasibility of the proposal is illustrated with two example cases, where the detailed explanation of the respective classification trees is shown
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
Decision tree classifiers have been proved to be among the most interpretable models due to their in...
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....
This study describes a model of explanations in natural language for classification decision trees....
Claims about the interpretability of decision trees can be traced back to the origins of machine lea...
Claims about the interpretability of decision trees can be traced back to the origins of machine lea...
Decision tree classifiers have been proved to be among the most interpretable models due to their in...
Decision tree classifiers have been proved to be among the most interpretable models due to their in...
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 thoroughly research the methods of construction of the deci...
After building a classifier with modern tools of machine learning we typically have a black box at h...
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
After building a classifier with modern tools of machine learning we typically have a black box at h...
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
Decision tree classifiers have been proved to be among the most interpretable models due to their in...
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....
This study describes a model of explanations in natural language for classification decision trees....
Claims about the interpretability of decision trees can be traced back to the origins of machine lea...
Claims about the interpretability of decision trees can be traced back to the origins of machine lea...
Decision tree classifiers have been proved to be among the most interpretable models due to their in...
Decision tree classifiers have been proved to be among the most interpretable models due to their in...
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 thoroughly research the methods of construction of the deci...
After building a classifier with modern tools of machine learning we typically have a black box at h...
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
After building a classifier with modern tools of machine learning we typically have a black box at h...
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
Fairness, Accountability, Transparency and Explainability have become strong requirements in most pr...
Decision tree classifiers have been proved to be among the most interpretable models due to their in...