main moduleΒΆ

Main script for running the experiments: python main.py --help displays tips about the command line options. Default options are found in the configuration.ini file.

Usage:

python main.py -N [1] -t [2] -d [3] -c [4] -ts [5] -s [6] -nmin [7] -nmax [8] -di [9] -p [10] -cs [11] -cc [12] -o [13] -te [14] -in [15] -g [16] -cfg [17] -v [18] --debug --help
where:
  • Default options are found in the configuration.ini file.
  • [1] -i, --iter: number of classification iterations.
  • [2] -t, --threads: number of cores to use.
  • [3] -d, --dataset: dataset to use.
  • [4] -c, --classifier: classifier to use.
  • [5] -ts, --trainsize: proportion of dataset to use for training.
  • [6] -s, --sim: similarity type to use.
  • [7] -nmin: minimum number of synthetic labels.
  • [8] -nmax: maximum number of synthetic labels.
  • [9] -di, --distrib: synthetic annotation mode (RND, UNI, OVA).
  • [10] -p, --post: post-processing task/algorithm.
  • [11] -cs, --cvg_step: check convergence criterion every cs step.
  • [12] -cc, --cvg_criterion: convergence criterion threshold.
  • [13] -o, --output: output folder.
  • [14] -te, --temp: temporary folder.
  • [15] -in: input data file.
  • [16] -g, --ground: ground-truth file.
  • [17] -cfg, --config_file: provide a custom configuration file.
  • [18] -v, --verbose: controls verbosity level (0 to 4).
  • -db, --debug: debug mode (save temporary files).
  • -h, --help

Main outputs:

  • output.log: log file
  • sim_matrix_final.npy: similarity matrix.

Verbosity levels:

  • -v 0: minimal verbose level; almost no printed trace.
  • -v 1: Default.
  • -v 2: Additional print trace.
  • -v 3: Prints out the classifier’s traces.
  • -v 4: Outputs additional result (distributions plots, number of occurences in test for each entity ...) + save similarity matrix regularly.