Business success prediction in Rwanda: a comparison of tree-based models and logistic regression classifiers

2021 ◽  
Vol 1 (8) ◽  
Author(s):  
Francis Kipkogei ◽  
Ignace H. Kabano ◽  
Belle Fille Murorunkwere ◽  
Nzabanita Joseph
Keyword(s):  
Logistic Regression ◽  
Success Prediction ◽  
Business Success

scholarly journals A Model for Business Success Prediction using Machine Learning Algorithms

2019 ◽  
Vol 1299 ◽  
pp. 012050
Author(s):  
Ibukun Afolabi ◽  
T. Cordelia Ifunaya ◽  
Funmilayo G. Ojo ◽  
Chinonye Moses
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Success Prediction ◽  
Business Success

Deep multi-task learning with relational attention for business success prediction

2021 ◽  
Vol 110 ◽  
pp. 107469
Author(s):  
Jiejie Zhao ◽  
Bowen Du ◽  
Leilei Sun ◽  
Weifeng Lv ◽  
Yanchi Liu ◽  
...  
Keyword(s):  
Success Prediction ◽  
Business Success ◽  
Task Learning

How Useful is the Power Law of Practice for Recognizing Practice in Concentration Tests?

2007 ◽  
Vol 23 (3) ◽  
pp. 157-165 ◽  
Author(s):  
Carmen Hagemeister
Keyword(s):  
Logistic Regression ◽  
Reaction Time ◽  
Power Law ◽  
Error Rate ◽  
Reaction Times ◽  
Practice Effect ◽  
Practice Effects ◽  
Rate Decrease ◽  
Small Practice

Abstract. When concentration tests are completed repeatedly, reaction time and error rate decrease considerably, but the underlying ability does not improve. In order to overcome this validity problem this study aimed to test if the practice effect between tests and within tests can be useful in determining whether persons have already completed this test. The power law of practice postulates that practice effects are greater in unpracticed than in practiced persons. Two experiments were carried out in which the participants completed the same tests at the beginning and at the end of two test sessions set about 3 days apart. In both experiments, the logistic regression could indeed classify persons according to previous practice through the practice effect between the tests at the beginning and at the end of the session, and, less well but still significantly, through the practice effect within the first test of the session. Further analyses showed that the practice effects correlated more highly with the initial performance than was to be expected for mathematical reasons; typically persons with long reaction times have larger practice effects. Thus, small practice effects alone do not allow one to conclude that a person has worked on the test before.

Perceived Effectiveness of Random Testing for Alcohol and Drugs in the Australian Aviation Community

2012 ◽  
Vol 2 (2) ◽  
pp. 72-81
Author(s):  
Christina M. Rudin-Brown ◽  
Eve Mitsopoulos-Rubens ◽  
Michael G. Lenné
Keyword(s):  
Logistic Regression ◽  
Online Survey ◽  
Random Testing ◽  
Regression Analyses ◽  
Perceived Effectiveness ◽  
Student Pilots ◽  
Alcohol And Drugs ◽  
Positive Attitudes ◽  
One Year ◽  
Alcohol And Other Drugs

Random testing for alcohol and other drugs (AODs) in individuals who perform safety-sensitive activities as part of their aviation role was introduced in Australia in April 2009. One year later, an online survey (N = 2,226) was conducted to investigate attitudes, behaviors, and knowledge regarding random testing and to gauge perceptions regarding its effectiveness. Private, recreational, and student pilots were less likely than industry personnel to report being aware of the requirement (86.5% versus 97.1%), to have undergone testing (76.5% versus 96.1%), and to know of others who had undergone testing (39.9% versus 84.3%), and they had more positive attitudes toward random testing than industry personnel. However, logistic regression analyses indicated that random testing is more effective at deterring AOD use among industry personnel.

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