Document classification using naive bayes algorithm (Kayıt no. 434)

MARC ayrıntıları
000 -BAŞLIK
Sabit Uzunluktaki Kontrol Alanı 04391na a2200973 4500
001 - KONTROL NUMARASI
Control Dosyası 233328
003 - KONTROL NUMARASI KİMLİĞİ
Kontrol Alanı koha_MIRAKIL
005 - EN SON İŞLEM TARİHİ ve ZAMANI
Kontrol Alanı 20221226090135.0
008 - SABİT UZUNLUKTAKİ VERİ ÖGELERİ - GENEL BİLGİ
Sabit Alan 190118b tu 000 0
040 ## - KATALOGLAMA KAYNAĞI
Özgün Kataloglama Kurumu CY-NiCIU
Kataloglama Dili tur
Çeviri Kurumu CY-NiCIU
Açıklama Kuralları rda
041 0# - DİL KODU
Metin ya da ses kaydının dil kodu eng
090 ## - Yerel Tasnif No
tasnif no YL 391
Cutter no A35 2014
100 1# - KİŞİ ADI
Yazar Adı (Kişi adı) Adi, Abdulwahab O.
245 0# - ESER ADI BİLDİRİMİ
Başlık Document classification using naive bayes algorithm
Sorumluluk Bildirimi Abdulwahab O. Adi; Supervisor: Erbuğ Çelebi
260 ## - YAYIN, DAĞITIM, VB.
Yayın Yeri Nicosia
Yayınevi Cyprus International University
Yayın Tarihi 2014
300 ## - FİZİKSEL TANIMLAMA
Sayfa, Cilt vb. IX, 49 p.
Diğer fiziki detaylar figure
Boyutları 30.5 cm
Birlikteki Materyal CD
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
500 ## - GENEL NOT
Materials specified Includes CD
520 ## - ÖZET NOTU
Özet notu 'ABSTRACT In this study, we have implemented a naïve Bayes Classifier in the Java Language. The classifier was tested on the popular 20 News group data set for majority of document categorization and clustering algorithm implementation. The ultimate object is for better understanding of the algorithm as an a way for automatic document categorization is done and also to be able to ponder new methods that can be proposed for future research purposes. At the end of this research, we successfully tested the performance of our implementation using three methods. The accuracy was measured by comparing it's with the accuracies of other algorithms using the same dataset. It turned out to work as postulated theoretically in normal academic environs. Also, we were able to conclude that the naïve Bayes classifier performs well among other similar classifiers but it also has its short comings as well. Keywords: Bayes Theorem, Supervised Learning, Document Classification, Naïve Bayes Classifier, Tokenization, Stemming, Machine Learning, Information Retrieval, Java '
650 00 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ
Konusal terim veya coğrafi ad Makine öğrenme
650 00 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ
Konusal terim veya coğrafi ad Machine learning
650 00 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ
Konusal terim veya coğrafi ad Bayes teoremi
650 00 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ
Konusal terim veya coğrafi ad Bayes Theorem
700 0# - EK GİRİŞ - KİŞİ ADI
Yazar Adı (Kişi adı) Supervisor: Çelebi, Erbuğ
9 (RLIN) 1656
942 ## - EK GİRİŞ ÖGELERİ (KOHA)
Sınıflama Kaynağı Dewey Onlu Sınıflama Sistemi
Materyal Türü Thesis
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 1
Title CHAPTER ONE
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 1
Title INTRODUCTION
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 3
Title Objectives
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 3
Title Organization of Thesis
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 4
Title CHAPTER 2
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 4
Title LITERATURE REVIEW
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 4
Title Machine Learning
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 5
Title Supervised Learning
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 7
Title Unsupervised Learning
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 7
Title Semi-Supervised Learning
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 8
Title Reinforcement Learning
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 8
Title Transduction
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 10
Title Learning to Learn
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 10
Title Developmental Learning
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 11
Title PREVIOUS WORK DONE
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 11
Title Naive Bayes Classifier As A Spam Detector
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 12
Title Naive Bayes Classifier in Sentiment Analysis
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 13
Title Naive Bayes Classifier in Cancer Diagnosis
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 14
Title Naive Bayes Classifier in Plant Specie classification
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 15
Title CHAPTER 3
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 15
Title NAİVE BAYES CLASSIFIER
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 15
Title Bayes Theorem
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 15
Title Text Classification Simplified
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 18
Title Prior Probability,P(c)
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 19
Title Likelihood Probability, Pd/c
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 20
Title Laplace Smoothening
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 22
Title Simple Text Classification Examples
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 26
Title CHAPTER 4
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 26
Title IMPLEMENTATION
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 26
Title Introduction
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 26
Title Java an NLP Libraries
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 27
Title Program Design
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 27
Title Experimental Setup
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 28
Title Loading the data set
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 29
Title Stop Word Removal
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 30
Title Tokenization
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 33
Title Stemming
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 36
Title Bag of Word Creation
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 39
Title Evaluation
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 39
Title Classification
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 40
Title Design Summary
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 41
Title CHAPTER 5
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 41
Title EVALUATION
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 41
Title Cross Validation method
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 41
Title Comparison with other Classifier Application
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 42
Title Icsiboost-bigram
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 42
Title Expected Maximum alorithm
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 42
Title Varied Training Set based Evaluation
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 43
Title RESULTS OF EVALUATION PROCEDURES
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 43
Title Cross Validation Method
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 44
Title Comparison with other Classifier Programs
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 45
Title Varied Training Set based Evaluation
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 46
Title CHAPTER 6
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 46
Title CONCLUSION AND FUTURE WORK
505 1# - İÇİNDEKİLER NOTU
Miscellaneous information 47
Title REFERENCES
Mevcut
Geri Çekilme Durumu Kayıp Durumu Sınıflandırma Kaynağı Kredi için değil Koleksiyon Kodu Kalıcı Konum Mevcut Konum Raf Yeri Kayıt Tarih Source of acquisition Maliyet, Alış Fiyatı Yer Numarası Demirbaş Numarası Son Görülme Tarihi Maliyet, Yenileme Fiyatı Fatura Tarihi Materyal Türü Genel / Bağış Notu
    Dewey Onlu Sınıflama Sistemi   Tez Koleksiyonu CIU LIBRARY CIU LIBRARY Tez Koleksiyonu 18.03.2014 Bağış 0.00 YL 391 A35 2014 T431 18.03.2014 0.00 18.03.2014 Thesis Information Systems Engineering Department
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