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CVUT-FS-12110/TBPFG

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TBPFG - Tensor-based Polynomial Features Generator

The algorithm of TBPFG is implemented in modules tbpf (numpy implementation) and tbpf_tf (tensorflow implementation up to pf degree 5).

Scripts in the root are for testing of algorithms performance.

  • tbpf_numpy.py - Numpy implementation of TBPFG
  • tbpf_tf_cpu.py - Tensorflow implementation of TBPFG, TF is forced to use CPU
  • tbpf_tf_gpu.py - Tensorflow implementation of TBPFG, TF will use GPU if it is available
  • pf_numpy.py - Simple recursive algorithm of PF generation
  • pf_scikit.py - Algorithm from scikit-learn library sklearn.preprocessing.PolynomialFeatures

All testing scripts are CMD-line scripts that write the results into the console and saves results into CSV file. The naming convention for results file is res_{script name}_d{degree}_it{number of iterations}.csv.

Input parameters of testing scripts are:

  • -h, --help show help message and exit
  • -d DEGREE, --degree DEGREE Degree of polynomial features
  • -i ITERATIONS, --iterations ITERATIONS Number of iterations over one number of inputs
  • --start START Number of inputs start
  • --stop STOP Number of inputs stop
  • --step STEP Number of inputs step

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