Zobrazeno 1 - 10 of 33 pro vyhledávání: '"Marvin L. Brown"'
1
Effects of the neural network s-Sigmoid function on KDD in the presence of imprecise data
Autor: Mike Lin, Marvin L. Brown, John F. Kros
Publikováno v: Computers & Operations Research. 33:3136-3149
This research explores a specific step in the Knowledge Discovery of Databases (KDD) process, Data Mining. The actual data mining process deals significantly with prediction, estimation, classification, pattern recognition and the development of asso
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e910c3cec29b8dc165e37beccdfbfd2c
https://doi.org/10.1016/j.cor.2005.01.024
Zobrazit plný text záznamu
2
Data mining and the impact of missing data
Autor: John F. Kros, Marvin L. Brown
Publikováno v: Industrial Management & Data Systems. 103:611-621
The actual data mining process deals significantly with prediction, estimation, classification, pattern recognition and the development of association rules. Therefore, the significance of the analysis depends heavily on the accuracy of the database
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2eae46cc61b60b2d345a6685ab574546
https://doi.org/10.1108/02635570310497657
Zobrazit plný text záznamu
3
Effects of Data Imputation Methods on Data Missingness in Data Mining
Autor: Chien-Hua Mike Lin, Marvin L. Brown
Publikováno v: GSTF INTERNATIONAL JOURNAL ON COMPUTING. 1
The purpose of this paper is to study the effectiveness of data imputation methods in dealing with data missingness in the data mining phase of knowledge discovery in Database (KDD). The application of data mining techniques without careful considera
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7a57f605511d712978cc6076e3c3c9e2
https://doi.org/10.5176/2010-2283_1.2.53
Zobrazit plný text záznamu
5
Imprecise Data and the Data Mining Process
Autor: John F. Kros, Marvin L. Brown
Publikováno v: Encyclopedia of Data Warehousing and Mining
Missing or inconsistent data has been a pervasive problem in data analysis since the origin of data collection. The management of missing data in organizations has recently been addressed as more firms implement large-scale enterprise resource planni
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e17e7a43935d56dd18b6c6c2ed424977
https://doi.org/10.4018/978-1-59140-557-3.ch112
Zobrazit plný text záznamu
6
The Impact of Missing Data on Data Mining
Autor: John F. Kros, Marvin L. Brown
Data mining is based upon searching the concatenation of multiple databases that usually contain some amount of missing data along with a variable percentage of inaccurate data, pollution, outliers, and noise. The actual data-mining process deals sig
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::627dc14e8889e7e0601a33286e35c2fc
https://doi.org/10.4018/978-1-59140-051-6.ch007
Zobrazit plný text záznamu
7
A comparison of imputation methods in the presence of imprecise data when employing a neural network s-Sigmoid function
Autor: John F. Kros, Marvin L. Brown
Publikováno v: International Journal of Business Intelligence and Data Mining. 2:292
This research addresses the effects of the neural network s-Sigmoid function on Knowledge Discovery of Databases (KDD) in the presence of imprecise data. ANOVA testing and Tukey's Honestly Significant Difference statistics are conducted to investigat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2d60d3d22fe935def80e48fcd1ce0252
https://doi.org/10.1504/ijbidm.2007.015486
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje