Bias-Variance Tradeoff Curve in Python, R, Julia and JavaScript

Source code in 15 libraries — Python: Altair, Bokeh, lets-plot, Matplotlib, Plotly, plotnine, Pygal, Seaborn; R: ggplot2; Julia: Makie.jl; JavaScript: Chart.js, D3.js, Apache ECharts, Highcharts, MUI X Charts.

A theoretical visualization of the bias-variance tradeoff showing how total prediction error decomposes into bias squared, variance, and irreducible noise as a function of model complexity. The plot displays multiple curves: bias squared (decreasing with complexity), variance (increasing with complexity), irreducible error (constant), and total error (U-shaped). This is one of the most fundamental conceptual plots in machine learning for understanding model selection, overfitting, and underfitting.

Renders

• Full-resolution render, light theme
• Full-resolution render, dark theme
• Interactive version, light theme
• Interactive version, dark theme

Preview render from the MUI X Charts implementation.

Implementations

• Bias-Variance Tradeoff Curve in Altair (Python)
• Bias-Variance Tradeoff Curve in Bokeh (Python)
• Bias-Variance Tradeoff Curve in lets-plot (Python)
• Bias-Variance Tradeoff Curve in Matplotlib (Python)
• Bias-Variance Tradeoff Curve in Plotly (Python)
• Bias-Variance Tradeoff Curve in plotnine (Python)
• Bias-Variance Tradeoff Curve in Pygal (Python)
• Bias-Variance Tradeoff Curve in Seaborn (Python)
• Bias-Variance Tradeoff Curve in ggplot2 (R)
• Bias-Variance Tradeoff Curve in Makie.jl (Julia)
• Bias-Variance Tradeoff Curve in Chart.js (JavaScript)
• Bias-Variance Tradeoff Curve in D3.js (JavaScript)
• Bias-Variance Tradeoff Curve in Apache ECharts (JavaScript)
• Bias-Variance Tradeoff Curve in Highcharts (JavaScript)
• Bias-Variance Tradeoff Curve in MUI X Charts (JavaScript)