Dataset Modification Improve Algorithm by Penchala Sathish (5 results)

Taschenbuch. Condition: Neu. Dataset Modification to improve ML algorithm performance and speed | A Key to improve Machine Learning performance | Sathish Kumar Penchala (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204733418 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We propose two pre-processing steps to classification that apply convex hull- based algorithms to the training set to help improve the performance and speed of classification. The Class Reconstruction algorithm uses a clustering algorithm combined with a convex hull-based approach that re-labels the dataset with a new and expanded class structure. We demonstrate how this performance- improvement algorithm helps boost the accuracy results of Naive Bayes in some, but not all, cases that use real-world datasets. 72 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Penchala Sathish KumarDr. Sathish Kumar Penchala has many articles on AIML and distinguished faculty and head for AIML at IIST, Indore Mr. Prateek Dutta is an aspiring student in AIML branch, leading project internship with foreign c.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -We propose two pre-processing steps to classification that apply convex hull- based algorithms to the training set to help improve the performance and speed of classification. The Class Reconstruction algorithm uses a clustering algorithm combined with a convex hull-based approach that re-labels the dataset with a new and expanded class structure. We demonstrate how this performance- improvement algorithm helps boost the accuracy results of Naive Bayes in some, but not all, cases that use real-world datasets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We propose two pre-processing steps to classification that apply convex hull- based algorithms to the training set to help improve the performance and speed of classification. The Class Reconstruction algorithm uses a clustering algorithm combined with a convex hull-based approach that re-labels the dataset with a new and expanded class structure. We demonstrate how this performance- improvement algorithm helps boost the accuracy results of Naive Bayes in some, but not all, cases that use real-world datasets.