Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
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:
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.
Types of validation controls provided by ASP.Net There are following types of validation controls provided by ASP.Net: 1. Required Field Validator 2. Compare Validator
specialization,ggeneralization and aggregation of railway reservation system?
Explain the generic framework for electronic commerce along with suitable diagram? Generic Framework for electronic commerce comprises the Applications of EC (as like banking,
Like ULINE the statement VLINE is used to insert vertical lines. No , Vline is not used to insert vertical lines.
The Boolean expression A‾.B + A.B‾ + A.B is equivalent to ? Ans. The Boolean expression A‾ .B + A. B‾+ A.B is equivalent to A + B (A‾ .B + A. B‾+ A.B = B( A‾ + A) + A. B‾ =
When calling an external report the parameters or select-options specified in the external report cannot be called.
Q. What is Multiple Interrupt Lines? Multiple Interrupt Lines: Simplest solution to problems above is to provide multiple interrupt lines that will result in immediate recognit
Determine the term- Security When using Internet, security can be enhanced using encryption. Debit and credit card transactions can also be protected by a specific type of pas
Explain about the two services that are used to deal with communication. Message Service: Used by the application servers to change short internal messages, all system commu
Write a main function that opens an ifstream on the input file, "person.dat". If the stream cannot be opened, output an error message and exit. The file format is as foll
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!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd