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NN.MDB
The Database that thinks
© 2007 Ben Margolis

Glossary

Terms in neural networking vary. Some people like to use biological words for everything, like neuron and synapse (I've even seen "soma," "axon" and "dendrite"). While at the newsgroup comp.ai.nn they don't even call them "neurons." Instead they call them "units." (Which means its really not a "neural network" anymore, wouldn't it be a "Unitarian Network?")

I personally have a problem with the word "network." It may have been accurate in the 50's for the hardwired perceptrons they were building then, but today it means "a computer network" and as soon as you say "neural network" to anyone outside the AI community, they they think you mean multiple computers.

That's why I started using the term "Neural Cluster" to describe the relatively small MLPs we can build in NN.MDB. (Actually I usually use the phrase "simulated neural cluster" when talking to clients.) I also prefer to call it a "run" instead of an "epoch" and "data" as opposed to "input set."

NN.MDB Term

Abriv.

Term used at Newsgroup Comp.AI.NN

Implementation in NN.MDB

Details

Neuron

n

Unit

A record in the Neural Table (nn1Neu)

Neural ID number (nID) its current value (charge), its weight, previous delta, x,y coord. etc.

Neural Cluster

NN

Neural Network

A record in the Network Table (tblNets), or the subset (query) of all neurons and synapse related to that record.

Network ID (NetID), MLP design, names of ext. data sources, training history

Synapse

Syn

Weighted Connection

A record in the Synaptic Table (nn1Syn).

Two nIDs, a NetID, layer and the synaptic weight.

Synaptic Layer

SynLyr

A subset of all the Synapse of the NN in the same layer, with their connected Neurons. (qryCurrNNSynLyr)

SynLyr1, contains Input and Hidden Neurons and Synapses, SynLyr2, contains Hidden and Output Neurons and Synapses.

FactData

Training Set

Any Access table or Query that contains training facts, with expected output.

 

TestData

Verification Set

Any Access table or editable Query that contains training facts, with blank columns for NN output and with expected output.

(usually a subset REMOVED from the FactData)

RunData

Any Access table or editable Query that contains runtime inputs with blank columns for NN output.

Actual runtime data source.

Run

Epoch

One full execution of any datasource through the NN

 

network architecture

The exact number of neurons in each layer of the NN

I:2, H:10, O:1 would mean 2 input Neurons, 10 hidden, and 1 output.


NN.MDB Website Navigation


     
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Features:

Native to Access:
easily reads all Access data without export, can be easily implemented in any Access app without external APIs.

A Great Primer for Access programmers who want an intro into Neural nets.

Neural Diagrams: See your network, watch it grow!

Shared Neurons: Build complex multi-tier networks.

 

  More info:

How It Works

How to Use It

   Walkthrough

NYI: Not Yet Implemented

The Interface

Versions 2 & 3

NN.ACCDB (The Access 2007 version)

Glossary

 

 

 

 

 

© 2009 Ben Margolis. All Rights Reserved.