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Why are "cause and effect" diagrams also called "fishbone diagrams" ?
What is a Fishbone Diagram?
A Fishbone diagram is also known as a Ishikawa diagram. It is so named because it looks like a fish's backbone.
Because an Ishikawa / cause-and-effect diagram can be plotted in a shape resembling a fishbone.
http://en.wikipedia.org/wiki/Ishikawa_diagram
because they resemble fish bones like in a whole fish.
See this for more http://en.wikipedia.org/wiki/Ishikawa_diagram
Because it doesn't look like a ham bone.
Ishikawa diagrams are useful in determining the breadth (or cause density) of a problem. Using a technique such as the "5 Whys" is useful for determining a problem's depth. Understanding both the depth and the breadth of a problem is fundamental in root cause analysis.
Because they look like a fishes skeleton / bones.
Use Why Tree or similar. Ishikawa and 5 Why are a pretty good introduction to RCA but are limited and often miss or overlook true root causes.
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Lets say that my definition of 'rudimentary programming' refers to the fundamental tools employed for a computer to perform a task.
Considering programming rudiments, the learning spectrum usually looks something like this:
Variables, data types and variable memory
Arrays/Lists and their manipulation
Looping and conditionals
Functions
Classes
Multi threading/processing
Streams (hard-disk and web)
My question is, have I missed any of the major rudiments? Is there a 'next' to the spectrum that still eludes me?
I think you missed the most important one: algorithms. Understanding the complexity, know the situation to use them, why use them and more important, how to implement them.
I'm pretty sure that you already know a lot about algorithms but if you think that your tool-knowledge (aka the programming languages) are good enough, you should start focus, more, on the algorithms.
A great book to start is: Introduction to Algorithms, from Thomas H. Cormen
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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'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 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.