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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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Is anybody aware of a concurrent version of Tarjan's SCCs algorithm, Kosaraju's algorithm or any other fast, O(|V| + |E|) algorithm for finding SCCs? Neither of those algorithms seem to be very hard to multithread, but I'd be happy for somebody else to have done this job.
What I'm trying to handle here is an 8 GB directed graph, which I keep in RAM using a big AWS instance, and I'd like to make a good use of all 16 cores.
That's possibly the best paper I have found so far, I'll have a go at the implementation. http://domino.research.ibm.com/library/cyberdig.nsf/1e4115aea78b6e7c85256b360066f0d4/d8e3597a4172437b8525709f006e42b0?OpenDocument
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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'm good at algorithms but not as good as converting real-time problems and learning them throughly to make it as an algorithm. I would like to know if there is any book/paper that teaches or makes you demystify the situation and formulate it as an algorithm. (Its much like training your mental ability to break the situation and comeup with algorithm in a crisp.)
Showing some of the ways to approach these kinda problems. and any easy learning links/material would help me a lot.
Note: I know SO doesnt allow to ask for the opinion or something vague (I dont mind my Q being downgraded). But I am asking some concrete problem and hope can get some nice info from some of the great minds here.
The word that fits better as a direct answer is "experience". There exists no magical formula to convert a real time problem into some algorithms that solve it. As an analogy, there exist no predefined patterns on how to solve a mathematical problem. It is a mind's task to express the solution, based on some fundamental knowledge and on experience that is accumulated though constant learning.
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This may not be question of programming and people are open to close.
Does anyone has list of questions/problems to solve which helps to improve algorithms skills
may be for interview purpose.
A good option is Project Euler.
In its own description:
Project Euler is a series of challenging mathematical/computer programming problems that will require more than just mathematical insights to solve. Although mathematics will help you arrive at elegant and efficient methods, the use of a computer and programming skills will be required to solve most problems.
The motivation for starting Project Euler, and its continuation, is to provide a platform for the inquiring mind to delve into unfamiliar areas and learn new concepts in a fun and recreational context.
This seems like a perfect match...
Try TopCoder. They have held hundreds of algorithm competitions. Their archive contains thousands of problems for practice, including editorials describing the solutions. You can also view other people's submitted source code for the problems.
This will certainly sharpen your algorithm and problem solving skills, which should make you better prepared for algorithmic interview questions.
Fizz-Buzz?