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I am building a decision tree. Now, I want to store splitting condition or threshold value, parent, leaf and other variable in a tree structure, so that I can call that again and get those values in time of prediction? I am not using any random-forest package as I want to get my tree as like I wish.
The list structure is the only way to go. Take a look at how the dendrogram objects are stored.
?as.dendrogram
The other package to review would be igraph.
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Hey I want to create a chemical structure editor like chem draw, I am using QT software with C++ programming to create one, so can you guide me how to create a structure and if we can attach different bond with it chem draw link: chemdraw
Well I create chemical structure using QPainter API but we can't attach bonds to it, I want something so that I can attack two structures to make a one
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When should one consider using a metamodel in place of an expensive analysis component? I haven't actually seen an example of an openMDAO project that uses metamodels yet, so I was wondering if they're recommended or whether it's still best to treat expensive analyses like normal ones.
Using a metamodel is a trade-off. You trade accuracy vs execution time so it is up to you in your context.
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How to advance edit distance with operation take an anagram of the existing word. every interim step must be a word from a list of words .
The standard technique for anagrams is to store words in canonical sorted order, e.g. "Banana" becomes "aaabnn". Do that for all valid words, then consider Levenshtein distances between those. You will want to map from canonical to a valid set, e.g. valid['dgo'] = {'dog', 'god'}
Take a look at tail /usr/share/dict/words if you need a set of valid words.
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I want to create a program which allow in html to read excel data and form a graph but I do not know how to do it.
Any idea how to do it? Possible then could you send me a link I can look to start the project?
Take a look at js-xlsx(https://github.com/SheetJS/js-xlsx) library using tha t you can parse excel files.
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Can you please provide a specific situation illustrating when a for loop might work more effectively than the more commonly cited apply suite of solutions?
If the results of the previous computation are used in the next computation, it is appropriate to use a for loop, since this behavior is difficult to replicate with lapply (you would have to use something like Reduce). R is not necessarily slow with for loops, merely with memory allocation (which is easy to get wrong with for loops). See Chapter 2 of the R Inferno.