… We propose a new model for supervised classification for data mining applications. This
model is based on products of trees. The information given by each predictor variable is …

… used in statistical data analysis, particularly in data mining. This paper describes decision
trees, their data structure and their implementation in statistical data analysis. Decision …

… pace of research in the data mining, motivated us to … trees for classification tasks (ie
classification trees). In this edition we describe how decision trees can be used for other data mining …

… In traditional applications of data mining, the volume of data is the main obstacle to the use
of memory-based techniques due the restrictions in the computational resources: memory, …

… and data mining. In this paper we will introduce a variety of Regression Tree data mining …
3 and explain how they are used to model nonlinear dependencies in insurance claim data. …

… ) is a well-known data mining activity. We exploit this correspondence to mine large pattern
matrices to generate compact abstractions in the form of trees. Such abstraction generation is …

… Data mining techniques such as decision trees have been employed by researchers for
treating problems in manufacturing. [2] developed a framework for classifying manufacturing …

… method (FHEDM) was tested using data from 148 products sourced from a design repository
[… repository data ‘learning’ is going to stem from data mining techniques rather than product …

… the categorical data. Besides this decision tree are also for processing a large amount of
data and thus find use in data mining applications. For constructing decision trees no domain …

… These observations prompted us to postulate that data-mining methods may be useful to …
the data-mining analysis using decision trees. The algorithms were constructed using the data …