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

Functions for mpi environment, Q. Functions for MPI Environment? Int M...

Q. Functions for MPI Environment? Int MPI_Finalize (void) It ends the MPI environment. Any MPI function cannot be called after MPI_Finalize. Each MPI process belongs to on

Discuss in detail the subscriber loop systems, Discuss in detail the subscr...

Discuss in detail the subscriber loop systems. Subscriber Loop System: Every subscriber in a telephone network is linked usually to the nearest switching office by means of w

Push and pop, i want flowchart for push, pop in stack element and display s...

i want flowchart for push, pop in stack element and display stack and exit

What all 1's represents in 32bit ip addressing scheme, In 32bit IP Addressi...

In 32bit IP Addressing scheme all 1's represent? All 1's represent limited broadcast in 32 bit IP Addressing scheme.

How are comparisons done in 8086 assembly language, Q. How are comparisons ...

Q. How are comparisons done in 8086 assembly language? There is a compare instruction CMP. Though this instruction just sets the flags on comparing two operands (both 16 bits

Ellipse follows the perimeter of the window, A) Execute a program where an ...

A) Execute a program where an ellipse follows the perimeter of the window. B)  Execute a program that can draw graphs, possibly following your plan from last week. Have it graph

Show the conditional jump in program with example, Q. Show the conditional ...

Q. Show the conditional jump in program? CMP    AX, BX                      ; compare instruction: sets flags JNE     FIX                             ; if not equal do addi

Use of hypertext links in internet access, Use of Hypertext links in Intern...

Use of Hypertext links in Internet access From the user's point of view, the Web having of a vast, worldwide collection of documents i.e. pages. Every page may have links (poin

What are models and meta models, Model: It is a entire explanation of s...

Model: It is a entire explanation of something (i.e. system). Meta model: It shows the model elements, syntax and semantics of the notation that permits their manipulatio

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