Abstract
Classification learning is an important research
topic in machine learning and data mining
disciplines. In our study, CUFP (Classification
by Using Feature Projections), a feature
projections-based incremental classificationlearning
algorithm, was developed. The training
phase of CUFP determines points and the
distribution of the training instances at each
point to the classes in the case of nominal feature
projections. For linear feature projections,
gaussian probability density functions are
constructed for each class. In the classification
phase, each feature projection distributes votes
among classes. The vote vectors of features are
evaluated according to some vote evaluation strategies and the query instance’s class is
predicted.
Abstract
Sınıflandırma öğrenilmesi makine öğrenmesi ve veri tabanı madenciliği disiplinlerinde önemli bir araştırma konusudur. Bu çalışmada ÖİKS (Öznitelik İzdüşümü Kullanılarak Sınıflandırma) öznitelik izdüşümü tabanlı, artımlı biçimde sınıflandırma öğrenen bir algoritma geliştirilmiştir. Algoritmanın öğretme bölümünde nominal öznitelikler için noktalar ve her bir noktaya düşen öğretme örneklerinin sınıflara dağılımı belirlenir. Nümerik özniteliklerde ise her bir sınıf için gaussian olasılık yoğunluğu fonksiyonları oluşturulur. Algoritmanın sorgulama (test) bölümünde ise her bir öznitelik izdüşümü oyunu sınıflar arasında bölüştürür. Özniteliklerin oy vektörleri belirli oy değerlendirme şekillerine göre kullanılıp, sorgu örneğinin sınıfı tahmin edilmeye çalışılır.
Details
| Other ID | JA37GA58RB |
|---|---|
| Journal Section | Makaleler(Araştırma) |
| Authors | |
| Publication Date | June 24, 2016 |
| Published in Issue | Year 2005 Volume: 1 Issue: 1 - Volume: 1 Issue: 1 |
Cite
Article Acceptance
Use user registration/login to upload articles online.
The acceptance process of the articles sent to the journal consists of the following stages:
1. Each submitted article is sent to at least two referees at the first stage.
2. Referee appointments are made by the journal editors. There are approximately 200 referees in the referee pool of the journal and these referees are classified according to their areas of interest. Each referee is sent an article on the subject he is interested in. The selection of the arbitrator is done in a way that does not cause any conflict of interest.
3. In the articles sent to the referees, the names of the authors are closed.
4. Referees are explained how to evaluate an article and are asked to fill in the evaluation form shown below.
5. The articles in which two referees give positive opinion are subjected to similarity review by the editors. The similarity in the articles is expected to be less than 25%.
6. A paper that has passed all stages is reviewed by the editor in terms of language and presentation, and necessary corrections and improvements are made. If necessary, the authors are notified of the situation.
.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.