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I'm looking for an explanation of the Kameda-Weiner algorithm.
I found the paper "On the State Minimization of Nondeterministic Finite Automata" which, I assume, contains this, though it's unfortunately behind a paywall, and I'm just a hobbyist.
Can someone explain the algorithm, or point me to another source?
Although I have absolutely no idea what you are talking about, I think these two pdf files contain some sort of explanation.
Link1
Link2
I just tried to answer it, because I know how frustrating it can be, when you something you really want is behind a paywall! Hope it helps.
Cheers!
It's implemented here: https://github.com/coder0xff/parlex_legacy/blob/132e4a23a599140d22b18ead832626f0c607340f/Automata/NFA.cs#L641
(updated to fix dead link)
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I've been working on a data mining project lately, and it confuses me a lot that alternating decision tree seems to have more accuracy than WEKA built-in j48 algorithm. I don't have much idea about how these two algorithms are implemented, I hope someone can explain this from the algorithm point of view. Thanks a lot.
I don't have much idea about how these two algorithms are implemented
No one can explain to you why one can perform better than the other if you don't even understand the starting points. Learn about C4.5 and then learn about ADTrees.
Otherwise this would be an exercise in trying to teach you two algorithms in a single giant post - which is futile.
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Imagine that you have ropes which are 5 meters long. And you want to cut the rope in some certain lengths(30 cm,73 cm) for some certain times. I want to write a program that minimize the total length of the excessed robe and tells you how you should cut every rope. But, I don't know where to start and use what algorithm. Can you give me some reference? Thank you in advance.
What you are looking for is so called Cutting stock problem.
Start by looking at this Wikipedia article and follow Suggested readings. I remember we had this as a part of some course back at the university (although I can't remember which one), so you could have a look at coursera.
Seems like homework, but I can still point you in the right direction. What you have on hand is an example of dynamic programming. From what I can understand from your question, you have a sub-case of the ever popular knapsack problem. Which is in essence an optimization problem of using the space on hand most efficiently, thus reducing the waste. Tweak it a bit to your own needs and you should be able to manage to get the solution for your problem.
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I have applied to couple of startups and most of them are asking to solve programming challenge before they start on the interviewing candidate.
I have submitted couple of the solution and all the time getting rejected in the initial screening.
Now what i think is, they will see my coding style, algorithm and OOD concepts that i have used to solve the problem. Can you guys input more on it as what other details are taken into consideration and how can i improve my coding for getting selected.
By the way, i did all my coding in either Java/Perl.
Nice question, I am a new grad too... One thing I notice: When you do the exercise home, they expect you to use the best algorithm out there. In my opinion code modularity, even on a small function is key. Put lot effort into the code because they are not just judging you, but comparing you against other candidate. The one which seems to have put the more effort wins.
ps: Ask this question on programmers.stackexchange, you will obtain some good inputs there.
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I came across the declaration in a software best practices guide that algorithm and code shouldn't get mixed up. I'm not sure what is meant by this? As far as I understand, code is the implementation of the algorithm, isn't is? So, what exactly is meant by this statement? and why it is considered as a good practice?
Thank You!
The context in which the author mentioned would be clearer if you had pasted the surrounding lines.
Though what it would mean to me is, an algorithm is just a clear step-by-step logic that you would use to implement. You would leave out the finer implementation details like selection of the right data structure and other implementation details while you write/design the algorithm.
A good explanation can be found here
An algorithm is a series of steps for solving a problem, completing a task or performing a calculation. Algorithms are usually executed by computer programs but the term can also apply to steps in domains such as mathematics for human problem solving.
Code is a series of steps that machines can execute. In many cases, code is composed in a high level language that is then automatically translated into instructions that machines understand.
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We are thinking of using a Wizard pattern to help a user complete a task.
The Wizard pattern seems to solve our problem. We are also interested in what human factors research might have to say about the basic problem of a non-expert user needing to accomplish an infrequent and complicated task-–-are there other, possibly better paradigms for doing this than a wizard?
You posted this question over two years ago and no one has offered a better interaction design pattern than the wizard.
That looks like an answer to me.