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Re: [ontolog-forum] Toward Human-Level AI

To: "'[ontolog-forum] '" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Rich Cooper" <rich@xxxxxxxxxxxxxxxxxxxxxx>
Date: Tue, 3 Jun 2014 17:56:41 -0700
Message-id: <44EAC14BFD5243BBA3BF2EED0A736443@Gateway>
After reading C4.5, it seems nearly identical to
ID3.  What exactly is the difference?      (01)

Sincerely,
Rich Cooper
EnglishLogicKernel.com
Rich AT EnglishLogicKernel DOT com
9 4 9 \ 5 2 5 - 5 7 1 2    (02)

-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On
Behalf Of Jack Park
Sent: Tuesday, June 03, 2014 5:11 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Toward Human-Level AI    (03)

FWIW, I implemented ID3 in Forth back in around
1984 to support a
friend's thesis research; it was used to evaluate
comments made by
manufacturing engineers on process control.    (04)

An issue it raised, which has been mentioned in
the literature, is
that it grew rather complex, bushy decision trees.
I think that might
be a part of the reason for migration to C4.5
http://en.wikipedia.org/wiki/C4.5_algorithm    (05)


On Sun, Jun 1, 2014 at 9:32 AM, Rich Cooper
<rich@xxxxxxxxxxxxxxxxxxxxxx> wrote:
> Here is a link to the ID3 algorithm by Ross
Quinlan:
>
> http://en.wikipedia.org/wiki/ID3_algorithm
>
>
>
> The algorithm iteratively divides the elements
of S based on all attribute
> values of all objects, which are said elements
of S.  So it picks the group
> of features and weights that make the most
"efficient" split.  That
> separates S into S0 and S1.  Its use of the
"entropy" analogy to evaluate
> efficiency of the split seems a bit of
anthropopathy.
>
>
>
> Has anyone used ID3 to identify classes in
clustering analysis?
>
>
>
> -Rich
>
>
>
> Sincerely,
>
> Rich Cooper
>
> EnglishLogicKernel.com
>
> Rich AT EnglishLogicKernel DOT com
>
> 9 4 9 \ 5 2 5 - 5 7 1 2
>
>
>
>
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