scholarly journals Data Mining Based on Principal Component Analysis: Application to the Nitric Oxide Response in Escherichia coli

2014 ◽  
Vol 2 (1) ◽  
Author(s):  
AiLing Teh ◽  
Donovan Layton ◽  
Daniel R. Hyduke ◽  
Laura R. Jarboe ◽  
Derrick K. Rollins ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Escherichia Coli ◽  
Data Mining ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Application

Data Mining in Analysis of Biomechanical Signals

2009 ◽  
Vol 147-149 ◽  
pp. 588-593 ◽  
Author(s):  
Marcin Derlatka ◽  
Jolanta Pauk
Keyword(s):  
Data Mining ◽  
Principal Component Analysis ◽  
Cerebral Palsy ◽  
Spina Bifida ◽  
Decision Tree ◽  
Principal Component ◽  
Data Preprocessing ◽  
Component Analysis ◽  
Kernel Principal Component Analysis

In the paper the procedure of processing biomechanical data has been proposed. It consists of selecting proper noiseless data, preprocessing data by means of model’s identification and Kernel Principal Component Analysis and next classification using decision tree. The obtained results of classification into groups (normal and two selected pathology of gait: Spina Bifida and Cerebral Palsy) were very good.

Improving Earthquake Prediction with Principal Component Analysis: Application to Chile

2015 ◽  
pp. 393-404 ◽  
Author(s):  
Gualberto Asencio-Cortés ◽  
Francisco Martínez-Álvarez ◽  
Antonio Morales-Esteban ◽  
Jorge Reyes ◽  
Alicia Troncoso
Keyword(s):  
Principal Component Analysis ◽  
Earthquake Prediction ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Application

Statistical approaches in literature: An application of principal component analysis and factor analysis to analyze the different arrangements about the Quran’s Suras

2020 ◽  
Author(s):  
Yanwen Wang ◽  
Javad Garjami ◽  
Milena Tsvetkova ◽  
Nguyen Huu Hau ◽  
Kim-Hung Pho
Keyword(s):  
Data Mining ◽  
Principal Component Analysis ◽  
Factor Analysis ◽  
Data Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Holy Quran ◽  
The Holy Quran ◽  
Statistical Approaches

Abstract Data mining, statistics, and data analysis are popular techniques to study datasets and extract knowledge from them. In this article, principal component analysis and factor analysis were applied to cluster thirteen different given arrangements about the Suras of the Holy Quran. The results showed that these thirteen arrangements can be categorized in two parts such that the first part includes Blachère, Davood, Grimm, Nöldeke, Bazargan, E’temad-al-Saltane and Muir, and the second part includes Ebn Nadim, Jaber, Ebn Abbas, Hazrat Ali, Khazan, and Al-Azhar.

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