کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
496457 | 862860 | 2007 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Unsupervised learning with normalised data and non-Euclidean norms
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Unsupervised learning with normalised data and non-Euclidean norms Unsupervised learning with normalised data and non-Euclidean norms](/preview/png/496457.png)
چکیده انگلیسی
The measurement of distance is one of the key steps in the unsupervised learning process, as it is through these distance measurements that patterns and correlations are discovered. We examined the characteristics of both non-Euclidean norms and data normalisation within the unsupervised learning environment. We empirically assessed the performance of the K-means, neural gas, growing neural gas and self-organising map algorithms with a range of real-world data sets and concluded that data normalisation is both beneficial in learning class structure and in reducing the unpredictable influence of the norm.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 7, Issue 1, January 2007, Pages 203–210
Journal: Applied Soft Computing - Volume 7, Issue 1, January 2007, Pages 203–210
نویسندگان
K.A.J. Doherty, R.G. Adams, N. Davey,