Implementation of decision tree algorithm on FPGA devices

<span id="docs-internal-guid-01e673b1-7fff-8dc3-6b99-14ed17cd6b49"><span>Machine learning techniques are rapidly emerging in large number of fields from robotics to computer vision finance and biology. One important step machine is classification which the process finding out category a new encountered observation belongs based on predefined categories. There various existing solutions one them decision tree (DTC) can achieve high accuracy while handling datasets. But DTC computationally intensive algorithm as size dataset increases its running time also could be some hours days even. thanks field programmable gate arrays (FPGA) used for datasets performance implementation with low energy consumption. Along FPGA’s, python accelerating application development leveraged by using productivity zynq (PYNQ), environment development. This paper provides literature review an FPGA devices along future work that done.</span></span>