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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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The documentation for Encoding Policy states that
The default indexing applied to string columns is built for term searches. If you only query for specific values in the column, COGS might be reduced if the index is simplified using the encoding profile Identifier. For more information, see the string data type.
How does the indexing for Identifier affects performance for hasPrefix, hasSuffix and regex matches? Is it inadequate to such queries?
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These day, I study the Information Retrieval(expecially about Text Retrieval).
and I want to make a Search engine. But I confused about the title things that Inverted Index and Vector Space Model(in addition, boolean model etc...for representing document as a vector)
I think Inverted Index is a optional function for Vector Space Model, since this indexing model can help program to get terms(or words) more effectively
.... this is my thinking... is right?
please any comment.
Document-term matrix and inverted index are ways to save documents.
After saving the documents you can use vector space model or language models as retrieval models of a search engine.
Also if you just need a search engine made with some data you have and implementing it from the beginning is not your point, you can use Apache Lucene.
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Suppose I have data frame A. If A[I,j]=="z", I want to delete column j. How to do this?
Do you mean for a specific row, or all rows? If the former, use:
A <- A[grepl('^z$', unlist(A[i,]))]
Where i is the row where the character 'z' is potentially located. If the latter, could just use a for loop to do across all i.
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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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I heard this a lot when talking about software engineering and abstract data types, what does this do? Can anyone give me a concrete example of this concept?
A representation invariant is a condition concerning the state of an object. The condition can always be assumed to be true for a given object, and operations are required not to violate it.
In a Deck class, a representation invariant might be that there are always 52 Cards in the deck. A shuffle() operation is thus guaranteed not to drop any cards on the floor. Which in turn means that someone calling shuffle(), or indeed any other operation, does not need to check the number of cards before and after: they are guaranteed that it will always be 52.