/SVM-Proliferation-NIPS2021

This repo contains codebase for "Support vector machines and linear regression onlycoincide with very high-dimensional features" paper.

Primary LanguagePythonMIT LicenseMIT

Support vector machines and linear regression coincide with very high-dimensional features

This repository is the official codebase of ASH21 . In order to reproduce our figures, we have provided the experiments which we used for the analyses alongside with the code to produce the experiments.

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Requirements

To install the requirements:

pip install -r requirements.txt

Our results were obtained in Python 3.8.5 environment.

Generate Datasets

Python files can be used to generate the datasets. Note that our code has the flexibility to run in parallel; number of cores can be specified, if not the code will run in a serialized fashion. The seed is not fixed in our code.

File Syntax Example
l1_svm.py python l1_svm.py <path_to_save_files> <num_cores> python l1_svm.py "./datasets_l1" 4
l2_suite.py python l2_suite.py <path_to_save_files> <num_cores> python l2_suite.py "./datasets_l2" 4

Analyses

The analyses are done in R where the R-markdown file is provided. Please make sure the path to datasets directories are correct (in case one changes the defaults).