Modeling, Visualization, and Analysis of African Innovation Performance

Autor:	Omer, Muhammad, El-Amin, Moayad, Nasr, Ammar, Ahmed, Rami
Rok vydání:	2020
Předmět:	Computer Science - Computers and Society Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	In this paper we discuss the concepts and emergence of Innovation Performance, and how to quantify it, primarily working with data from the Global Innovation Index, with emphasis on the African Innovation Performance. We briefly overview existing literature on using machine learning for modeling innovation performance, and use simple machine learning techniques, to analyze and predict the "Mobile App Creation Indicator" from the Global Innovation Index, by using insights from the stack-overflow developers survey. Also, we build and compare models to predict the Innovation Output Sub-index, also from the Global Innovation Index. Comment: 4 pages, 3 figures, Appeared as a poster presentation at the Practical Machine Learning for Developing Countries workshop in the 2020 International Conference on Learning Representation (ICLR), formerly Addis Ababa, held virtually, slides and corresponding video for virtual sessions can be found at: https://pml4dc.github.io/iclr2020/program/pml4dc_47.html
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2008.07882 Zobrazit plný text záznamu View this record from Arxiv