Dear dash,

Kindly refer to the following papers:

1. Cox, D. R. (2018). Analysis of binary data. Routledge.

2. Assunção, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya, R. (2015). Big Data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 79, 3-15.

3. Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big data and its technical challenges. Communications of the ACM, 57(7), 86-94.

4. Junqué de Fortuny, E., Martens, D., & Provost, F. (2013). Predictive modeling with big data: is bigger really better?. Big Data, 1(4), 215-226.

5. Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234-246.

Thanks,

Sobhan

Hi,

Try all of them and then make the decision.

HTH.

Dr. Samer Sarsam

I suggest for reading related article in link

http://www.msquared.com/wp-content/uploads/2017/01/A-Simple-Framework-for-Building-Predictive-Models.pdf

Dear dash,

Kindly refer to the following papers:

1. Cox, D. R. (2018). Analysis of binary data. Routledge.

2. Assunção, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya, R. (2015). Big Data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 79, 3-15.

3. Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big data and its technical challenges. Communications of the ACM, 57(7), 86-94.

4. Junqué de Fortuny, E., Martens, D., & Provost, F. (2013). Predictive modeling with big data: is bigger really better?. Big Data, 1(4), 215-226.

5. Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234-246.

Thanks,

Sobhan

That depends on your problem at hand. Sounds like you want to train a classifier. It is good practice to begin with a simple one such as Bayesian or kNN and see how well it performs. If the accuracy is insufficient, go for a more sophisticated one such as SVM or Logit.

Thank you all for your valuable suggestions.