| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta http-equiv="Content-Type" content="text/html;charset=utf-8"/> | |
| <title>US Electoral Map</title> | |
| <link rel="stylesheet" href="style.css"/> | |
| <link rel="stylesheet" href="http://code.jquery.com/mobile/1.2.0/jquery.mobile-1.2.0.min.css" /> | |
| <script src="http://d3js.org/d3.v2.min.js?2.10.1"></script> | |
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| sepalLength | sepalWidth | petalLength | petalWidth | species | |
|---|---|---|---|---|---|
| 5.1 | 3.5 | 1.4 | 0.2 | setosa | |
| 4.9 | 3.0 | 1.4 | 0.2 | setosa | |
| 4.7 | 3.2 | 1.3 | 0.2 | setosa | |
| 4.6 | 3.1 | 1.5 | 0.2 | setosa | |
| 5.0 | 3.6 | 1.4 | 0.2 | setosa | |
| 5.4 | 3.9 | 1.7 | 0.4 | setosa | |
| 4.6 | 3.4 | 1.4 | 0.3 | setosa | |
| 5.0 | 3.4 | 1.5 | 0.2 | setosa | |
| 4.4 | 2.9 | 1.4 | 0.2 | setosa |
Sometimes you need to show a tooltip over a different element than the one firing the mouseover event. Fortunately, d3-tip allows you to do that by passing an SVGElement as the second parameter to tip.show(). Like this:
tip.show(data, target)This SVGElement will be the new target of the tooltip.
K-means is a simple unsupervised machine learning algorithm that groups a dataset into a user-specified number (k) of clusters. The algorithm is somewhat naive--it clusters the data into k clusters, even if k is not the right number of clusters to use. Therefore, when using k-means clustering, users need some way to determine whether they are using the right number of clusters.
One method to validate the number of clusters is the elbow method. The idea of the elbow method is to run k-means clustering on the dataset for a range of values of k (say, k from 1 to 10 in the examples above), and for each value of k calculate the sum of squared errors (SSE). Like this:
var sse = {};
for (var k = 1; k <= maxK; ++k) {
sse[k] = 0;
clusters = kmeans(dataset, k);
clusters.forEach(function(cluster) {
mean = clusterMean(cluster);
A simple heatmap of node positions over the course of a force-directed layout algorithm. Click and drag nodes to see the heatmap update.
Forked from Mike Bostock's force-directed layout example.
A heatmap of node positions over the course of a force-directed layout algorithm, using 2D kernel density estimation (KDE) with the Gaussian kernel to determine heatmap values. Compare with a heatmap that does not use KDE.
This network is the mobile patent suit data.
| license: gpl-3.0 | |
| height: 600 | |
| license: gpl-3.0 | |
| height: 400 | |
| license: gpl-3.0 | |
| height: 500 | |
| license: gpl-3.0 | |
| height: 800 | |