In data visualization, an Andrews plot or Andrews curve is a way to visualize structure in high-dimensional data. It is basically a rolled-down, non-integer version of the Kent–Kiviat radar m chart, or a smoothed version of a parallel coordinate plot. It is named after the statistician David F. Andrews.[1] [2] [3] [4]
A value
x
Rd
x=\left\{x1,x2,\ldots,xd\right\}
fx(t)=
x1 | |
\sqrt2 |
+x2\sin(t)+x3\cos(t)+x4\sin(2t)+x5\cos(2t)+ …
This function is then plotted for
-\pi<t<\pi
-\pi
\pi
\left(
1 | |
\sqrt2 |
,\sin(t),\cos(t),\sin(2t),\cos(2t),\ldots\right)
If there is structure in the data, it may be visible in the Andrews curves of the data.
These curves have been utilized in fields as different as biology, neurology, sociology and semiconductor manufacturing. Some of their uses include the quality control of products, the detection of period and outliers in time series, the visualization of learning in artificial neural networks, and correspondence analysis.
Theoretically, it is possible to project them onto an n-sphere. The projection onto the circle results in the aforementioned radar chart.