Tuesday, March 30, 2010

Kohonen’s Self Organizing Maps in Excel/VBA, applied for reducing dimensions of colors and of financial ratios from Google Finance

Kohonen’s Self Organizing Maps (SOM) is a type of artificial neural network that is trained using unsupervised learning. The number of dimensions is effectively reduced as a two-dimensional, discrete representation of high-dimensional data is produced. A neighborhood function is used as the topological properties of the input space are preserved.

In this file, the output space is visualized in a 40x40 block of Excel cells that are colored appropriately. If you would like to take a look at a good description of the algorithm, go to AIJunkie’s website.

The second file, chooses three financial indicators – ROE, Debt-to-Equity and Market Capitalization – and once again depicts this three-dimensional data on a two-dimensional SOM. The ratios are from telecom sector of Google Finance and are (0,1) normalized beforehand. As the initial plot is “dominated” by the three biggest companies – for which a substantial portion of the entire space is reserved (the market capitalization ratio is extremely right skewed) – a logarithm transformation is later undertaken. The colors of the graph are unappealing, because the ratio vectors are used as RGB components of Excel cell colors :).


Robert said...


very nice post an a really great blog you are running here. I am glad I finally found it!

I did something similar using Microsoft Excel to implement the elatic net approach for TSPs (Durbin & Willshaw). Thought you might be interested. Here is the link:


Let me know what you think.

Kind regards


Ulrich Steinlechner said...

for marked research I would try the Kohonen Map.
I designed a new car and I Like to compare the efficient cars on the marked.
My goal is to compare the following specefications of a car:

1st Technical features that define
a. Has two seats
b. Has 1 seat
c. Has three seats
d. Has four seats
e. electric drive
f. Has three wheels
g. Has four wheels
h. If lighter than 200 kg
i. weighs 200 to 400 kg
j. Weighs about 400 kg
k. reach of small 50 km
l. Rechweite small 100 km
m. Small range 150 km
n. range exceeding 400 km
o. Has the front crumple zone
p. Has side crumple zone
q. Has rear crumple zones
r. Is made of metal
s. is built from plastic
2nd Market-specific characteristics
a. Is available in Germany
b. Is available in Europe
c. Is erhältllich in Asia
d. Is erhältllich in USA
e. Is available worldwide
f. A to 10 vehicles
g. 10-50 vehicles
h. 50-200 vehicles
i. 200-1000 Vehicles
j. 1000-10000 vehicles
k. more than 10,000 vehicles
l. concept
m. is prototype
n. is in series testing
Twin series with EU Homologation
3rd Consumption
a. define (yet, kWh per person per 100 km per vehicle with two people)
b. Petrol fuels
c. Diesel fuels
d. alcohol fuels
e. energy gas
f. hydrogen energy
g. woodfuels
h. energy battery
i. energy battery and capacitor
j. Own solar cell
k. Separate full hybrid generator
l. Can recuperate
4th Performance
a. maximum speed
b. Cruising speed
c. Stopping distance
d. Beschleunugung 00-50
e. ..
5th Design
a. doors
b. Transparent nose with light

is it possible to create a SOM with this specificatons of cars?

Greetings from Germany
Ulrich Steinlechner


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