Description

In this episode, I pondered the problem of false positives in publications, rotated around the JuliaHub, machinated over machine learning projects, and put R package ‘drawCell’ to the test.

References:

• Are most published research findings false in a continuous universe?
• Principal component analysis
• A no-free-lunch theorem for multitask learning
• JuliaHub
• Signal-to-noise ratio and statistical tests
• Large Enough Sample Condition
• Top 11 Interesting Machine Learning Project Ideas For 2023
• Code longevity of the R programming language
• {drawCell} – R package and Shiny app for drawing cell structures

R-packages:

• colorRamp2: Generate Color Mapping Functions
• rworkflows: Test, Document, Containerise, and Deploy R Packages
• MetChem: Chemical Structural Similarity Analysis
• panelsummary: Create Publication-Ready Regression Tables with Panels
• arf: Adversarial Random Forests