Add to ORKGAbstract—In order to solve the problem of how to improve the scalability of data processing capabilities and the data availability which encountered by data mining techniques for Data-intensive computing, a new method of tree learning is presented in this paper. By introducing the MapReduce, the tree learning method based on SPRINT can obtain a well scalability when address large datasets. Moreover, we define the process of split point as a series of distributed computations, which is implemented with the MapReduce model respectively. And a new data structure called class distribution table is introduced to assist the calculation of histogram. Experiments and results analysis shows that the algorithm has strong processing capabilities of da...
Abstract—The growing computerization in modern academic and industrial sectors is generating huge vo...
In this paper, we present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a d...
Classification is an important data mining problem. Although datasets can be quite large in data min...
Abstract Data-intensive computing has received substantial attention since the arrival of the big da...
One of the important problems in data mining is classification. Recently there has been a lot of int...
Classification is an important data mining problem. Although classification is a wellstudied problem...
Abstract—In this paper, we discuss a Grid data mining system based on the MapReduce paradigm of comp...
Implementation of machine learning algorithms in a distributed environment ensures us multiple advan...
Learning decision trees against very large amounts of data is not practical on single node computer...
In this age of Big Data, machine learning based data mining methods are extensively used to inspect ...
Abstract: Cloud computing provides cheap and efficient solutions of storing and analyzing mass data....
Data mining is the process of discovering interesting and useful patterns and relationships in large...
With the emergence of big data, inducting regression trees on very large data sets became a common d...
Today, we are living in a data-exploding era, in which the volume of data is expanding in an unbelie...
Data mining is nontrivial extraction of implicit, previously unknown and potential useful informatio...
Abstract—The growing computerization in modern academic and industrial sectors is generating huge vo...
In this paper, we present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a d...
Classification is an important data mining problem. Although datasets can be quite large in data min...
Abstract Data-intensive computing has received substantial attention since the arrival of the big da...
One of the important problems in data mining is classification. Recently there has been a lot of int...
Classification is an important data mining problem. Although classification is a wellstudied problem...
Abstract—In this paper, we discuss a Grid data mining system based on the MapReduce paradigm of comp...
Implementation of machine learning algorithms in a distributed environment ensures us multiple advan...
Learning decision trees against very large amounts of data is not practical on single node computer...
In this age of Big Data, machine learning based data mining methods are extensively used to inspect ...
Abstract: Cloud computing provides cheap and efficient solutions of storing and analyzing mass data....
Data mining is the process of discovering interesting and useful patterns and relationships in large...
With the emergence of big data, inducting regression trees on very large data sets became a common d...
Today, we are living in a data-exploding era, in which the volume of data is expanding in an unbelie...
Data mining is nontrivial extraction of implicit, previously unknown and potential useful informatio...
Abstract—The growing computerization in modern academic and industrial sectors is generating huge vo...
In this paper, we present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a d...
Classification is an important data mining problem. Although datasets can be quite large in data min...