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bootstrapping

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Data Analytics and Machine Learning in R. Linear-regression, Logistic-regression, Hierarchical-clustering, Boosting, Bagging, Random-forests, K-means-clustering, K-nearest-neighbors (K-N-N), Tree-pruning, Subset-selection, LDA, QDA, Support Vector Machines (SVM)

  • Updated Mar 25, 2021
  • R

Contains inferential statistical practices for machine learning models and analyses. Using Python and developing statistical thinking to work with a limited sample of data and be able to generate predictions about it. Applying confidence intervals to estimate unknown values. Using bootstrapping to simulate data acquisition repeatedly. Developmen…

  • Updated Sep 11, 2022
  • Jupyter Notebook

I collected dataset related to COVID-19 disease in various dimensions and presented here. You can read its details in "Adaptive Elastic-net Sliced Inverse Regression to Identify Risk Factors Affecting COVID-19" article. Also, here are the codes for the proposed method.

  • Updated Apr 6, 2023
  • R

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