As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references,or expertise, but this question will likely solicit debate, a
I\'m using LIBSVM for regression analysis.Works like a champ.But a 3-parameter grid search to optimize parameters for the model maxes out all four cores on my 2.66 GHz Intel box, and I still have to w
This is more like a general, brainstroming query rather than a question. So here it goes. Suppose, I have 1000 items which I can sell on a website at any given day.
I have encountered a very unusual problem. I have a set of phrases (noun phrases) extracted from a large corpus of documents. These phrases are >=2 and <=3 words of length. There is a need to clust
Which open-source package is the best for clustering a large corpus of documents? It should either decide the number of clusters by itself or it can also accept that as a parameter.
I need to code a Maximum Likelihood Estimator to estimate the mean and variance of some toy data.I have a vector with 100 samples, created with numpy.random.randn(100). The data should have zero mean
I\'m still pretty new to R and AI / ML techniques. I would like to use a neural net for prediction, and since I\'m new I would just like to see if this is how it should be done.
I wonder if it is possible to pass object weights along with features in Waffle开发者_如何转开发s supervised learners (e.g. decision trees) for boosting purposes?This does not appear to be possible, b
I wonder what kind of seed selection methods I can apply to K-means 开发者_如何学编程algorithm. Google search wasn\'t that helpful. Any suggestions?The seeds depend on the domain. For example, if your
If we have a set of M words, and know the similarity of the meaning of each pair of words in advance (have a M x M matrix of similarities), which algorithm ca开发者_JAVA百科n we use to make one k-dime
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