Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Feature Projections"'
Autor:
Murat Cakir, H. Altay Güvenir
Publikováno v:
Expert Systems with Applications
Expert Systems with Applications: an international journal
Expert Systems with Applications: an international journal
Cataloged from PDF version of article. Voting features based classifiers. shortly VFC. have been shown to perform well on most real-world data sets They are robust to irrelevant features and missing feature values. In this paper, we introduce an exte
Autor:
Aynur A. Dayanik
Publikováno v:
Expert Systems with Applications
Expert Systems with Applications: an international journal
Expert Systems with Applications: an international journal
This paper aims at designing better performing feature-projection based classification algorithms and presents two new such algorithms. These algorithms are batch supervised learning algorithms and represent induced classification knowledge as featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04d6a13dc8fad498e21e92c7a3ed8be5
https://hdl.handle.net/11693/21564
https://hdl.handle.net/11693/21564
Autor:
Öztürk, Ceyda Nur
Son 20 yılda gezgin robot navigasyonu amaçlı bilgisayarlı görme sahasında birçok araştırma yapılmıştır. Gerektirdiği hesaplama yüküne ve sonar ya da lazerli mesafe algılayıcılarla karştırıldığında ortamın geometrisini dolayl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_____10208::c9183f2776a9abd3054265b83e98fe10
https://acikbilim.yok.gov.tr/handle/20.500.12812/615856
https://acikbilim.yok.gov.tr/handle/20.500.12812/615856
Autor:
H. Altay Güvenir, Ilhan Uysal
Publikováno v:
Knowledge-Based Systems
Cataloged from PDF version of article. This paper describes a machine learning method, called Regression on Feature Projections (RFP), for predicting a real-valued target feature, given the values of multiple predictive features. In RFP training is b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbeb895a5a7900b47d2eefcde6f8c52d
https://hdl.handle.net/11693/25048
https://hdl.handle.net/11693/25048
Autor:
Gedikli, Eyüp
Güvenilir, hızlı ve otomatik şekilde, kimlik tespiti ve doğrulaması yapabilen biyometrik sistemler, kriminal vakalarda ve güvenlik gerektiren alanlarda, biyometrik özellikleri ilgi odağı haline getirmiştir. Son zamanlarda yüz ve yürüyü
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_____10208::c7e3fff14b47d53c11ee282c344bdad9
https://acikbilim.yok.gov.tr/handle/20.500.12812/480967
https://acikbilim.yok.gov.tr/handle/20.500.12812/480967
Autor:
Guvenir, H. Altay, Cakir, Murat
Voting features based classifiers. shortly VFC. have been shown to perform well on most real-world data sets They are robust to irrelevant features and missing feature values. In this paper, we introduce an extension to VFC. called voting features ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ce3e3bd5c9900472d112b885434afb48
https://aperta.ulakbim.gov.tr/record/28081
https://aperta.ulakbim.gov.tr/record/28081
Autor:
H. Altay Güvenir, Ilhan Uysal
Publikováno v:
Applied Intelligence
A new instance-based learning method is presented for regression problems with high-dimensional data. As an instance-based approach, the conventional method, KNN, is very popular for classification. Although KNN performs well on classification tasks,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e83c8228711a354cc733bb2f659b5792
https://hdl.handle.net/11693/24272
https://hdl.handle.net/11693/24272
Autor:
Emeksiz, Narin
oz ÇOKLU SINIF OYLAMASI İLE MİDE TÜMÖRÜ TEŞHİSİ Emeksiz, Narin Yüksek Lisans, Bilgisayar Mühendisliği Bölümü Tez Yöneticisi: Doç. Dr. Nihan Kesim Çiçekli Ortak Tez Yöneticisi : Prof. Dr. Halil Altay Güvenir Temmuz 2001, 86 sayfa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_____10208::ad85214a8a5b8e184bb6af862eaf21dc
https://acikbilim.yok.gov.tr/handle/20.500.12812/256910
https://acikbilim.yok.gov.tr/handle/20.500.12812/256910
Autor:
Uysal, İlhan
ÖZET ÖZNİTELİK İZDÜŞÜMLERİNİN PARÇALANMASI İLE ÖRNEKLERE DAYALI REGRESYON ilhan Uysal Bilgisayar Mühendisliği, Yüksek Lisans Tez Yöneticisi: Doç. Dr. Halil Altay Güvenir Ocak, 2000 Yüksek öznitelik sayılarına sahip verilerin re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8d930324fdc95b1b17d92f54dc828703
https://hdl.handle.net/11693/18250
https://hdl.handle.net/11693/18250
Autor:
Aydın, Tolga
ÖZET EN İYİ ÖZNİTELİKLERİ SEÇME İLE REGRESYON Tolga Aydın Bilgisayar Mühendisliği, Yüksek Lisans Tez Yöneticisi: Doç. Dr. Halil Altay Güvenir Eylül, 2000 Regresyon problemleri için, En İyi Öznitelik izdüşümlerini Seçerek Regre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::7d6797532bee5124c77603d252cf5fb9
https://acikbilim.yok.gov.tr/handle/20.500.12812/36849
https://acikbilim.yok.gov.tr/handle/20.500.12812/36849