Overview
The following example using kernel density estimation to estimate a sine curve from a number of noisy observations.Code
let dn = await import('/lib/machine-learning/kernel/v1.0.0/density.mjs');
let kl = await import('/lib/machine-learning/kernel/v1.0.0/kernel.mjs');
let data = $from(1,10,100).map(p=>{
return {
x:p,
y:Math.sin(p)+0.1*Math.random()
}
});
kernel = kl.epanechnikov(0.5);
let estimator = dn.estimator(data.map(p=>[p.x,p.y]), kernel);
let test = estimator(5);
Try it!
The following shows the estimator of the noisy sine curve example above.