Heterogeneous system parallel random forest optimization method and system

A random forest and heterogeneous system technology, applied in the field of machine learning, can solve problems such as long time to find the optimal solution and inability to process large data, so as to speed up the time to find the optimal solution and improve the system efficiency

Inactive Publication Date: 2015-11-11
INSPUR BEIJING ELECTRONICS INFORMATION IND
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Problems solved by technology

[0004] However, using the existing technology, it takes a long time to find the optimal solution in the process of data optimization. In the current era of exponential growth in the amount of data, it is obvious that the processing of very large data is powerless.

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  • Heterogeneous system parallel random forest optimization method and system
  • Heterogeneous system parallel random forest optimization method and system

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Embodiment Construction

[0017] In order to make the purpose, technical solution and advantages of the present invention more clear, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined arbitrarily with each other.

[0018] The steps shown in the flowcharts of the figures may be performed in a computer system, such as a set of computer-executable instructions. Also, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

[0019] The heterogeneous system parallel random forest optimization system involved in the embodiment of the present invention is applied to a mixed heterogeneous cluster of a central processing unit and a coprocessor, specifically a computer cluster or a ...

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Abstract

The invention discloses a heterogeneous system parallel random forest optimization system and method. The heterogeneous system parallel random forest optimization system is applied to a central processing unit and a coprocessor mixed heterogeneous cluster and comprises one master node and multiple slave nodes, wherein the main master node is used for dividing a data file to be calculated into multiple data fragments and transmitting the data fragments to all the slave nodes respectively; all the slave nodes are used for receiving the data fragments distributed by the master node to calculate the data fragments and transmitting a calculated optimal solution building decision-making tree to the master node to generate a random forest. As the data fragments are calculated by the slave nodes in parallel, the time for searching for the optimal solution is shortened, efficiency of the whole system is substantially improved, the system is unnecessarily limited by network bandwidth deficiency, small memory capacity and other conditions, and the requirement for processing large-scale data of high-performance application is met.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a heterogeneous system parallel random forest optimization system and method. Background technique [0002] In recent years, with the rapid development of today's social economy and technology, many application fields are rapidly accumulating a large amount of data, and analyzing these data to discover the information contained in the data has become a common demand in almost all fields. In practical applications, The role of machine learning in data mining analysis technology is becoming more and more important, and it has received extensive attention. [0003] In the prior art, the most commonly used classification method in machine learning is the random forest algorithm. Random forest is a supervised ensemble learning classification technology, which improves the prediction accuracy of the model by summarizing a large number of classification trees. It is precisely because of...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
Inventor 王娅娟张广勇吴韶华沈铂卢晓伟张清
Owner INSPUR BEIJING ELECTRONICS INFORMATION IND
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