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Supporting Vector Machine Classsfications Using High-Level Synthesis

C 2.79% Objective-C 0.73% C++ 46.49% LLVM 17.60% Tcl 0.61% Makefile 0.08% Verilog 3.63% Ada 9.58% Batchfile 0.01% Ruby 0.01% HTML 7.73% VHDL 10.65% Pascal 0.01% SystemVerilog 0.01% Coq 0.02% Stata 0.02% Shell 0.01% Forth 0.01% JavaScript 0.01% Scala 0.05%

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svm_hls_on_zynq's Issues

Classification with other dataset

Hello,

Thanks for this great project.
I was curious to use this for a multiclass SVM (on MNIST dataset) on ZCU104 board .
I trained the SVM model using SVM_light where I get a model file and a predictions file.
The model file contains the information regarding the training dataset like the size of the data used for training. It also contains information like the number of Support Vectors and their values, number of features, the bias value and the type of kernel used for training.
The predictions file contains all the values before applying the sign function of the decision function. These values are used for assigning the class which the test instance belongs to.
Can you guide me what are the steps for testing this using the given output files from svm_light ?

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