Advanced search    

Search: authors:"John Mingers"

7 papers found.
Use AND, OR, NOT, +word, -word, "long phrase", (parentheses) to fine-tune your search.

Using Google Scholar institutional level data to evaluate the quality of university research

In recent years, the extent of formal research evaluation, at all levels from the individual to the multiversity has increased dramatically. At the institutional level, there are world university rankings based on an ad hoc combination of different indicators. There are also national exercises, such as those in the UK and Australia that evaluate research outputs and environment...

Normalizing Google Scholar data for use in research evaluation

Using bibliometric data for the evaluation of the research of institutions and individuals is becoming increasingly common. Bibliometric evaluations across disciplines require that the data be normalized to the field because the fields are very different in their citation processes. Generally, the major bibliographic databases such as Web of Science (WoS) and Scopus are used for...

An Empirical Comparison of Pruning Methods for Decision Tree Induction

JOHN MINGERS 0 Jaime Carbonell 0 School of Industrial and Business Studies, University of Warwick , Coventry CV4 7AL, England This paper compares five methods for pruning decision trees, developed

An Empirical Comparison of Selection Measures for Decision-Tree Induction

One approach to induction is to develop a decision tree from a set of examples. When used with noisy rather than deterministic data, the method involves three main stages – creating a complete tree able to classify all the examples, pruning this tree to give statistical reliability, and processing the pruned tree to improve understandability. This paper is concerned with the...

An empirical comparison of selection measures for decision-tree induction

One approach to induction is to develop a decision tree from a set of examples. When used with noisy rather than deterministic data, the method involve-three main stages—creating a complete tree able to classify all the examples, pruning this tree to give statistical reliability, and processing the pruned tree to improve understandability. This paper is concerned with the first...