By N. R. Shetty, N.H. Prasad, N. Nalini
This lawsuits quantity covers the complaints of ERCICA 2015. ERCICA presents an interdisciplinary discussion board for researchers, specialist engineers and scientists, educators, and technologists to debate, debate and advertise examine and expertise within the upcoming components of Computing, info, communique and their functions. The contents of this ebook hide rising learn components in fields of Computing, details, verbal exchange and purposes. it will end up worthy to either researchers and practising engineers.
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In our case we have used Mutual information to select feature set, followed by trial and error method to conﬁgure the system to work better. Thus in training process every token of each tweet with labelling information is undergone with mutual information feature selection method, which gives us the probabilities of each token with respect to labels. The tokens with highest probabilities and their labels are added in ﬁnal token/training set . Hence the fundamental idea of feature selection algorithm is that, it searches through all possible combinations of attributes/keywords in the tweets to ﬁnd the subset of features works best for prophecy.
Supervised and Unsupervised Learning AI Horizon 5. : Unsupervised feature selection using feature similarity. IEEE Trans. Pattern Anal. Mach. Intell. C. B. Angadi 6. Miller, Subset Selection in Regression, Chapman & Hall/CRC, 2nd edn (2002) 7. com/t/twitters-search-api-and-user-application-authentication-cananyone-clarify-my-concerns/1188 8. : Feature Selection Using a Mutual Information Based Measure, pp. 1051–4651/02. IEEE (2002) 9. htm 10. 014 (2012) 11. : Is naïve bayes a good classiﬁer for document classiﬁcation?