comparison considering accuracy, error rate, precision and various related factors.....
This is a very well elaborated paper that covers most of the classifiers: http://jmlr.org/papers/volume15/delgado14a/delgado14a.pdf
You can use this tool for validation (Cluster Validation Toolbox Cvap v3.42 ).
This tool can bve used for both internal as well as external measure and it is available at MATH WORK website .
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before embarking into the jungle of papers comparing the animals of the classifier zoo, you might invest ten minutes reading the following :
http://arxiv.org/pdf/math/0606441.pdf
Hand D.J. (2006) Classifier technology and the illusion of progress. Statistical Science, 21, 1-34.
although i would not fully agree with the very abrupt conclusion of the author, i think this provocative paper is a useful reminder of all that is left outside of most if not all those" zoological" studies
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Dear Vaishali,
You can check the papers on topic identification applied to Arabic texts:
- M. Abbas, K. Smaili, D. Berkani. (2010). TR-Classifier and kNN Evaluation for Topic Identification Tasks. Special Issue on Advances in Arabic Language Processing, the International Journal on Information and Communication Technologies (IJICT), Vol 3, N 3, pp. 65-74, Serial Publications.
- M. Abbas, K. Smaili, D. Berkani. (2011). Evaluation of Topic Identification Methods on Arabic Corpora. Journal of Digital Information Management Vol. 9 No. 5, pp.185-192.
- M. Abbas, K. Smaili, D. Berkani, "Evaluation of Topic Identification Methods for Arabic Texts and their Combination by using a Corpus Extracted from the Omani Newspaper Alwatan." Arab Gulf Journal of Scientific Research 29.3-4 (2011): 183-191.
Regards
Mourad
) Comparing classification algorithm in data mining , Sampson Adu-Poku , Master thesis.
2) A Comparison Study between Data Mining Algorithms over Classification Techniques in Squid Dataset, Article
You can also refer following papers:
1. Classification Accuracy Performance of Naïve Bayesian (NB), Bayesian Networks (BN), Lazy Learning of Bayesian Rules (LBR) and Instance-Based Learner (IB1) – Comparative Study
2. A Comparative Study of Selected Classifiers with Classification Accuracy in User Profiling
3. Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy
There is a compaeission in the link
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.259.3668&rep=rep1&type=pdf
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