• usp_easy_retunsاسترجاع مجاني وسهل
  • usp_best_dealsأفضل العروض
placeholder
Fusion Methods For Unsupervised Learning Ensembles hardcover english
magnifyZoom

Fusion Methods For Unsupervised Learning Ensembles hardcover english

جنيه1390.00
nudge icon
باقي 1 وحدات في المخزون
nudge icon
باقي 1 وحدات في المخزون
noon-marketplace
احصل عليه خلال 16 يوليو
اطلب في غضون 3 ساعة 31 دقيقة

خصم على الدفع

decorative

إدفع 3 اقساط شهرية بقيمة ٤٦٣٫٣٣ جنيه.

placeholder
/cib-noon-credit-card
نظرة عامة على المنتج

المواصفات

الناشرSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
رقم الكتاب المعياري الدولي 103642162045
اللغةالإنجليزية
عدد الصفحات141
رقم الكتاب المعياري الدولي 139783642162046
تنسيق الكتابغلاف صلب
وصف الكتابThe application of a "committee of experts" or ensemble learning to artificial neural networks that apply unsupervised learning techniques is widely considered to enhance the effectiveness of such networks greatly. This book examines the potential of the ensemble meta-algorithm by describing and testing a technique based on the combination of ensembles and statistical pca that is able to determine the presence of outliers in high-dimensional data sets and to minimize outlier effects in the final results. Its central contribution concerns an algorithm for the ensemble fusion of topology-preserving maps, referred to as weighted voting superposition (wevos), which has been devised to improve data exploration by 2-d visualization over multi-dimensional data sets. This generic algorithm is applied in combination with several other models taken from the family of topology preserving maps, such as the som, visom, sim and max-sim. A range of quality measures for topology preserving maps that are proposed in the literature are used to validate and compare wevos with other algorithms. The experimental results demonstrate that, in the majority of cases, the wevos algorithm outperforms earlier map-fusion methods and the simpler versions of the algorithm with which it is compared. All the algorithms are tested in different artificial data sets and in several of the most common machine-learning data sets in order to corroborate their theoretical properties. Moreover, a real-life case-study taken from the food industry demonstrates the practical benefits of their application to more complex problems.
مجموع السلة 1390.00 جنيه
placeholder
Fusion Methods For Unsupervised Learning Ensembles hardcover english
Fusion Methods For Unsupervised Learning Ensembles hardcover english
جنيه1390.00
جنيه 1390
الكمية قليل: باقي 1 فقط
0

نحن دائماً جاهزون لمساعدتك

تواصل معنا من خلال أي من قنوات الدعم التالية:

تسوق أينما كنت

App StoreGoogle PlayHuawei App Gallery

تواصل معنا

mastercardvisavaluamexcod