fanglingwang

fanglingwang's Stars

• Atharva-Peshkar/Covid-19-Patient-Health-Analytics

  A Boosted Random Forest Classification model was implemented to predict the outcome of the CoV-2 positive patients in China. Based on multiple features.

  Language:Jupyter Notebook1931

• Soumyajit-Saha/Cosine-Similarity-based-Harmony-Search-Algorithm

  Language:MATLAB1

• wilsonjr/SHAP_FSelection

  Using SHAP values as feature selection mechanism

  Language:Python194

• steppenwolf0/miRNAs100

  Automatic Discovery of 100-miRNA Signature for Cancer Classification Using Ensemble Feature Selection

  Language:Mathematica3

• riken-aip/pyHSICLasso

  Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data

  Language:Python17142

• jimy2020/SFLA_IWSSr-Feature-Selection

  Feature selection problem is one of the most significant issues in data classification. The purpose of feature selection is selection of the least number of features in order to increase accuracy and decrease the cost of data classification. In recent years, due to appearance of high-dimensional datasets with low number of samples, classification models have encountered over-fitting problem.

  Language:C++103

• Fruktus/artifishswarm

  Implementation of AFSA algorithm

  Language:Python11