P-Prism: A computationally efficient approach to scaling up classification rule induction
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
P-Prism: A Computationally Efficient Approach
FT Stahl, MA Bramer, M Adda - … INTELLIGENCE IN THEORY AND PRACTICE II - Springer
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
[PDF][PDF] P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
FT Stahl, MA Bramer, M Adda - maxbramer.org.uk
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
P-Prism: a computationally efficient approach to scaling up classification rule induction
F Stahl, M Adda, M Bramer - Artificial Intelligence in Theory …, 2008 - researchportal.port.ac.uk
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
[PDF][PDF] P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
FT Stahl, MA Bramer, M Adda - dl.ifip.org
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
[PDF][PDF] P-Prism: A Computationally Efficient Approach
FT Stahl, MA Bramer, M Adda - academia.edu
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
[PDF][PDF] P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
FT Stahl, MA Bramer, M Adda - pure.port.ac.uk
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
[PDF][PDF] P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
FT Stahl, MA Bramer, M Adda - opendl.ifip-tc6.org
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
[PDF][PDF] P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
FT Stahl, MA Bramer, M Adda - core.ac.uk
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …
[PDF][PDF] P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
FT Stahl, MA Bramer, M Adda - researchgate.net
Abstract Top Down Induction of Decision Trees (TDIDT) is the most commonly used method
of constructing a model from a dataset in the form of classification rules to classify previously …
of constructing a model from a dataset in the form of classification rules to classify previously …