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A Set of Datasets Used in My Classes or in the Book 'Modele Liniowe i Mieszane w R, Wraz z Przykladami w Analizie Danych'
A set of datasets and functions used in the book 'Modele liniowe i mieszane w R, wraz z przykladami w analizie danych'. Datasets either come from real studies or are created to be as similar as possible to real studies.
Datasets and Functions Used in the Book 'Przewodnik po Pakiecie R'
Data sets and functions used in the polish book "Przewodnik po pakiecie R" (The Hitchhiker's Guide to the R). See more at < http://biecek.pl/R>. Among others you will find here data about housing prices, cancer patients, running times and many others.
Data Driven Smooth Tests
Smooth testing of goodness of fit. These tests are data driven (alternative hypothesis is dynamically selected based on data). In this package you will find various tests for exponent, Gaussian, Gumbel and uniform distribution.
Local Interpretable (Model-Agnostic) Visual Explanations
Interpretability of complex machine learning models is a growing concern.
This package helps to understand key factors that drive the
decision made by complicated predictive model (so called black box model).
This is achieved through local approximations that are either based on
additive regression like model or CART like model that allows for
higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016)
Explaining and Visualizing Random Forests in Terms of Variable Importance
A set of tools to help explain which variables are most important in a random forests. Various variable importance measures are calculated and visualized in different settings in order to get an idea on how their importance changes depending on our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran Z. Gorodeski and Andy J. Minn and Michael S. Lauer (2010)
Testing Differences Between Competing Risks Models and Their Visualisations
Tool for analyzing competing risks models. The main point of interest is testing differences between groups (as described in R.J Gray (1988)
Tools for Archiving, Managing and Sharing R Objects via GitHub
The extension of the 'archivist' package integrating the archivist with GitHub via GitHub API, 'git2r' packages and 'httr' package.
Stochastic Gradient Descent log-Likelihood Estimation in Cox Proportional Hazards Model
Estimate coefficients of Cox proportional hazards model using stochastic gradient descent algorithm for batch data.
Model Audit - Verification, Validation, and Error Analysis
Provides an easy to use unified interface for creating validation plots for any model. The 'auditor' helps to avoid repetitive work consisting of writing code needed to create residual plots. This visualizations allow to asses and compare the goodness of fit, performance, and similarity of models.