resampling-methods

Spatiotemporal resampling methods for mlr3

Solutions of applied exercises contained in "An Introduction to Statistical Learning with Applications in Python", by Tibshirani et al, edition 2023

R package cross-validation, bootstrap, permutation, and rolling window resampling techniques for the tidyverse.

A MATLAB package for multivariate permutation testing and effect size measurement

Resampling tools for openPMD PIC data.

Analysis and preprocessing of the kdd cup 99 dataset using python and scikit-learn

Stanford Online course STATSX0001 "Statistical Learning" follows closely the sequence of chapters in the course text "An Introduction to Statistical Learning, with Applications in R" (James, Witten, Hastie, Tibshirani - Springer 2013). Trevor Hastie Professor of Statistics and of Biomedical Data Sciences, Stanford University, and Robert Tibshira…

Credit risk poses a classification problem that’s inherently imbalanced. Using a dataset of historical lending activity from a peer-to-peer lending services company, build a model that can identify the creditworthiness of borrowers.

Statistical inference, hypothesis testing, ANOVA, correlation, and regression across datasets, including checks of statistical assumptions.

Importance of HBA1c in predictive Modeling of probability of Hospital Re-admission (CAPSTONE PROJECT)

Resampling procedure for weakly dependent stationary observations.

CLI Image Processing and Editing Suite

Resampling procedure for weakly dependent stationary observations.

Constructs a continuous-time function from a list of real numbers.

In this project, we perform exploratory analysis on the data and try out different models to give the best results.

A small C library for computation of U-statistics

Mathematical and statistical applications for HP Prime.

To Detect Early Sepsis Disease