So in summary, spectral clustering builds an affinity matrix of the data points.

In addition, it's multi spectral.

Identical in shape, size, spectral content.

We now talk about spectral clustering.

Taking form of a giant spectral dog.

Let me illustrate this once again with the data set that has a different spectral clustering than a conventional clustering.

Mass communication and mass transit.

Realtime audio processor based on frequency spectral manipulation

Mass

mass

For instance, you see the spectral line of the gold is the only spectral line in the spectrum of the Sun.

This is called affinity based clustering or spectral clustering.

less mass than all mass in stars.

Mass Conversions

Ball mass

Maximum mass

Minimum mass

Mass Storage

Equivalent Mass

Mass Calculator

Atomic mass

Atomic Mass

Exact Mass

Isotope mass

Atomic mass

Particle mass

Body mass

mass variance

CRlTICAL MASS

Mass production?

Mass winnings.

Spectral partitioning, L1 minimization. This comes from the optimization community.

They'll need a spectral micrometer to see it's a fabrication.

Data, data, data...

Bing! That's data. Data, data, data.

Now the key element of spectral clustering is called the affinity martrix, which is a 9 by 9 matrix in this case, where each data point gets graphed realtive to each other data point.

The fundamental idea of spectral clustering is to cluster by affinity.

So spectral clustering gets annotation of affinity to make clustering happen.

Mass rename files

Mass Storage Device

Mass storage controller

Atomic Mass u

Atomic Mass Unit

M is mass.

A mass murderer.