Arbitrary categorisation - learning decision trees, Computer Engineering

Assignment Help:

Arbitrary categorisation - learning decision trees:

Through visualising  a set of boxes with some balls in. There if all the balls were in a single box so this would be nicely ordered but it would be extremely easy to find a particular ball. Moreover If the balls were distributed amongst the boxes then this would not be so nicely ordered but it might take rather a whereas to find a particular ball. It means if we were going to define a measure based at this notion of purity then we would want to be able to calculate a value for each box based on the number of balls in it so then take the sum of these as the overall measure. Thus we would want to reward two situations: nearly empty boxes as very neat and boxes just with nearly all the balls in as also very neat. However this is the basis for the general entropy measure that is defined follows like: 

Now next here instantly an arbitrary categorisation like C into categories c1, ..., cn and a set of examples, S, for that the proportion of examples in ci is pi, then the entropy of S is as: 

198_Arbitrary categorisation - learning decision trees.png

Here measure satisfies our criteria that is of the -p*log2(p) construction: where p gets close to zero that is the category has only a few examples in it so then the  log(p) becomes a big negative number and the  p  part dominates the calculation then the entropy works out to be nearly zero. However make it sure that entropy calculates the disorder in the data in this low score is good and as it reflects our desire to reward categories with few examples in. Such of similarly if p gets close to 1 then that's the category has most of the examples in so then the  log(p) part gets very close to zero but it  is this that dominates the calculation thus the overall value gets close to zero. Thus we see that both where the category is nearly  -  or completely  -  empty and when the category nearly contains as - or completely contains as  - all the examples and the score for the category gets close to zero that models what we wanted it to. But note that 0*ln(0) is taken to be zero by convention them.


Related Discussions:- Arbitrary categorisation - learning decision trees

Biological motivation - two layer artificial neural networks, Biological Mo...

Biological Motivation : However remember there that in discussion first lecture is about how people have answered the question like: "How are we going to get an agent to proce

What do you mean by best fit, What do you mean by best fit?  Best fit a...

What do you mean by best fit?  Best fit allocates the smallest hole that is big enough. The whole list has to be searched, unless it is sorted by size. This method makes the sm

The 2''s complement of the decimal number, What is the 2's complement of th...

What is the 2's complement of the number 1101101 ? Ans. 0010011 is the 2's complement of the number 1101101. As 1's complement of the number 1101101 is 0010010 and 2's comple

Procedure level- levels of parallel processing, Procedure Level Here, p...

Procedure Level Here, parallelism is accessible in the form of parallel executable procedures. In this situation, the design of the algorithm plays a main role. For example eac

Explain about com add-ins, COM add-ins are software program's which are inc...

COM add-ins are software program's which are included into an application and they add already built in features to an existing application. They have general architecture across m

What do you mean by work flow automation, What do you mean by work flow aut...

What do you mean by work flow automation? Work Flow Automation: Organizations frequently standardize processes across the association and encourage users to accept them. E

What is control function, Q. What is control function? If transfer is t...

Q. What is control function? If transfer is to take place only under a predetermined control condition then this condition can be specified as a control function. For illustrat

State the advantages off-the-shelf, State the advantages Off-the-shelf ...

State the advantages Off-the-shelf -  tends to be less expensive as development costs can be spread over many users -  can be more sophisticated as large sales bring in c

What is cache memory, Q. What is Cache Memory? Cache memory is a very f...

Q. What is Cache Memory? Cache memory is a very fast and small memory between CPU and main memory whose access time is closer to processing speed of CPU. It behaves as a high-s

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd