Dynamic selection of normalization techniques using data complexity measures

2018 ◽  
Vol 106 ◽  
pp. 252-262 ◽  
Author(s):  
Sukirty Jain ◽  
Sanyam Shukla ◽  
Rajesh Wadhvani
Author(s):  
Luis P. F. Garcia ◽  
Ana C. Lorena ◽  
Marcilio C. P. de Souto ◽  
Tin Kam Ho

2018 ◽  
Vol 3 (1) ◽  
pp. 001
Author(s):  
Zulhendra Zulhendra ◽  
Gunadi Widi Nurcahyo ◽  
Julius Santony

In this study using Data Mining, namely K-Means Clustering. Data Mining can be used in searching for a large enough data analysis that aims to enable Indocomputer to know and classify service data based on customer complaints using Weka Software. In this study using the algorithm K-Means Clustering to predict or classify complaints about hardware damage on Payakumbuh Indocomputer. And can find out the data of Laptop brands most do service on Indocomputer Payakumbuh as one of the recommendations to consumers for the selection of Laptops.


2014 ◽  
Vol 28 (2) ◽  
pp. 261-276 ◽  
Author(s):  
Fei Kang

SYNOPSIS This study examines how family firms' unique ownership structure and agency problems affect their selection of industry-specialist auditors. Using data from Standard & Poor's (S&P) 1500 firms, the results show that family firms are more likely to appoint industry-specialist auditors than non-family firms, which suggests that family firms have strong incentives to signal the quality of financial reporting. Additional analysis indicates that due to the potential entrenchment problems, family firms with family member CEOs or with dual-class shares have even a higher tendency to hire industry-specialist auditors to signal their disclosure quality.


Sign in / Sign up

Export Citation Format

Share Document