✦ LIBER ✦

Detection and Localization of Myocardial Infarction using K-nearest Neighbor Classifier

✍ Scribed by Muhammad Arif; Ijaz A. Malagore; Fayyaz A. Afsar

Book ID: 106422088
Publisher: Springer US
Year: 2010
Tongue: English
Weight: 283 KB
Volume: 36
Category: Article
ISSN: 0148-5598
DOI: 10.1007/s10916-010-9474-3

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Simultaneous feature selection and featu

Simultaneous feature selection and feature weighting using Hybrid Tabu Search/K-nearest neighbor classifier

✍ Muhammad Atif Tahir; Ahmed Bouridane; Fatih Kurugollu 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 594 KB

Using optimized evidence-theoretic K-nea

Using optimized evidence-theoretic K-nearest neighbor classifier and pseudo-amino acid composition to predict membrane protein types

✍ Hongbin Shen; Kuo-Chen Chou 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 326 KB

Connectivity of the mutual k-nearest-nei

Connectivity of the mutual k-nearest-neighbor graph in clustering and outlier detection

✍ M.R. Brito; E.L. Chávez; A.J. Quiroz; J.E. Yukich 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 610 KB

For multivariate data sets, we study the relationship between the connectivity of a mutual k-nearest-neighbor graph, and the presence of clustering structure and outliers in the data. A test for detection of clustering structure and outliers is proposed and its performance is evaluated in simulated

Automatic Classification of Asymptomatic

Automatic Classification of Asymptomatic and Osteoarthritis Knee Gait Patterns Using Kinematic Data Features and the Nearest Neighbor Classifier

✍ Mezghani, N.; Husse, S.; Boivin, K.; Turcot, K.; Aissaoui, R.; Hagemeister, N.; 📂 Article 📅 2008 🏛 IEEE 🌐 English ⚖ 287 KB

Ideal bootstrap estimation of expected p

Ideal bootstrap estimation of expected prediction error for k-nearest neighbor classifiers: Applications for classification and error assessment

✍ Brian M. Steele; David A. Patterson 📂 Article 📅 2000 🏛 Springer US 🌐 English ⚖ 99 KB

Using particle swarms for the developmen

Using particle swarms for the development of QSAR models based on K-nearest neighbor and kernel regression

✍ Walter Cedeño; Dimitris K. Agrafiotis 📂 Article 📅 2003 🏛 Springer Netherlands 🌐 English ⚖ 167 KB