决策树分类器的FPGA实现

K. Kumari, D. Jhariya
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引用次数: 0

摘要

提出了一种基于FPGA的决策树分类器的实现方法。框架接受逗号分隔的值格式,然后执行许多步骤来形成训练好的模型。随后,该框架形成了两种基于决策树的分类器格式:Joint Photographic Experts Group和Verilog/VHDL。生成树的层次结构采用JPEG(图像)表示,并使用VHDL /Verilog代码作为训练模型硬件描述的表示。当前的框架在FPGA设计验证流程中使用Verilog/VHDL。这个新颖的框架弥补了mll模型训练和硬件设计之间的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Decision Tree Classifier on FPGA
This paper proposed the implementation of decision tree classifier on FPGA. A comma separated value format is accepted by the framework and then it does many steps to form a trained model. Subsequently the framework forms two formats of decision tree based classifier viz Joint Photographic Experts Group and Verilog/VHDL. The hierarchy of generated tree is represented by JPEG (image) representation and VHDL /Verilog code is used as a the representation of trained model hardware description. The current framework uses the Verilog/VHDL in FPGA DESIGN VALIDATION FLOW. The novelty framework bridges the gap between M.L. model training and its hardware designing.
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