Add to ORKGThe process of developing applications of machine learning and data mining that employ supervised classification algorithms includes the important step of knowledge verification. Interpretable output is presented to a user so that they can verify that the knowledge contained in the output makes sense for the given application. As the development of an application is an iterative process it is quite likely that a user would wish to compare models constructed at various times or stages. One crucial stage where comparison of models is important is when the accuracy of a model is being estimated, typically using some form of cross-validation. This stage is used to establish an estimate of how well a model will perform on unseen data. This is ...
In practical machine learning, models are frequently updated, or corrected, to adapt to new datasets...
This work deals with the classification methods used in the knowledge discovery from data process an...
Recent advances in machine learning and artificial intelligence are now beingconsidered in safety-cr...
Decision Tree (DT) typically splitting criteria using one variable at a time. In this way, the final...
In machine learning data usage is the most important criterion than the logic of the program. With v...
Decision trees are one of the most powerful and commonly used supervised learning algorithms in the ...
Tree-based discrimination methods provide a way of handling classification and discrimination proble...
<p>Diagnostic performance of a decision tree model with both training and validation datasets.</p
Background and aims. Machine learning models are trained using appropriate learning algorithm and tr...
Abstract: Decision Tree is a classification method used in Machine Learning and Data Mining. One maj...
Machine learning models have many applications, being used for example in pattern analysis, image cl...
The expansion of machine learning to high-stakes application domains such as medicine, finance, and ...
This paper studies model diagnostics for linear regression models. We propose two tree-based procedu...
Data mining is for new pattern to discover. Data mining is having major functionalities: classificat...
This work introduces methods and associated software for enhancing the interpretability of fitted mo...
In practical machine learning, models are frequently updated, or corrected, to adapt to new datasets...
This work deals with the classification methods used in the knowledge discovery from data process an...
Recent advances in machine learning and artificial intelligence are now beingconsidered in safety-cr...
Decision Tree (DT) typically splitting criteria using one variable at a time. In this way, the final...
In machine learning data usage is the most important criterion than the logic of the program. With v...
Decision trees are one of the most powerful and commonly used supervised learning algorithms in the ...
Tree-based discrimination methods provide a way of handling classification and discrimination proble...
<p>Diagnostic performance of a decision tree model with both training and validation datasets.</p
Background and aims. Machine learning models are trained using appropriate learning algorithm and tr...
Abstract: Decision Tree is a classification method used in Machine Learning and Data Mining. One maj...
Machine learning models have many applications, being used for example in pattern analysis, image cl...
The expansion of machine learning to high-stakes application domains such as medicine, finance, and ...
This paper studies model diagnostics for linear regression models. We propose two tree-based procedu...
Data mining is for new pattern to discover. Data mining is having major functionalities: classificat...
This work introduces methods and associated software for enhancing the interpretability of fitted mo...
In practical machine learning, models are frequently updated, or corrected, to adapt to new datasets...
This work deals with the classification methods used in the knowledge discovery from data process an...
Recent advances in machine learning and artificial intelligence are now beingconsidered in safety-cr...