Classification of Al-Hadith Al-Shareef using data mining algorithm
Source of Publication
Proceedings of the European, Mediterranean and Middle Eastern Conference on Information Systems: Global Information Systems Challenges in Management, EMCIS 2010
In this paper we compared the effectiveness of four different automatic learning algorithms for classifying Al-Hadith Al-Shareef into 8 selective books depending on Sahih BuKhari.The automatic learning algorithms are Rocchio algorithm, K-NN algorithm (K- Nearest Neighbor), Naïve Bayes algorithm and SVM algorithm (Support Vector Machines). We used TF-IDF technique to compute the relative frequency for each word in a particular document. We split the documents of AL-Hadith in such 75% of AL-Hadiths (1350 Hadiths) are used as training data (build the classifier) and the remaining 25% of AL-Hadith (150 Hadiths) are used for testing the accuracy of the resulting models in reproducing the manual category assignments.The average of words in each document is about 5to10 words.
Al-Hadith Al-Shareef, Bayes, Data mining, KNN, Rachio, SVM, Text classification
Alkhatib, Manar, "Classification of Al-Hadith Al-Shareef using data mining algorithm" (2010). All Works. 933.
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