Machine Intelligence for Predicting New Start-ups Success

Author:

Mishra Ajai1,Jat Dharm Singh1,Mishra Durgesh Kumar2

Affiliation:

1. Computer Science, Namibia University of Science and Technology, Windhoek, Namibia

2. Computer Science and Engineering, Sri Aurobindo Institute of Technology, Indore, India

Publisher

ACM

Reference24 articles.

1. 2021 Startup India Hub https://www.startupindia.gov.in/ 2021 Startup India Hub https://www.startupindia.gov.in/

2. The Federation of Indian Chambers of Commerce & Industry https://ficci.in/ The Federation of Indian Chambers of Commerce & Industry https://ficci.in/

3. Pujari, Arun K., "Data Mining Techniques" , Universities press , 2001 . Pujari, Arun K., "Data Mining Techniques", Universities press, 2001.

4. K. Żbikowski P. Antosiuk "A machine learning bias-free approach for predicting business success using Crunch base data" Information Processing and Management 58 (2021) 102555 K. Żbikowski P. Antosiuk "A machine learning bias-free approach for predicting business success using Crunch base data" Information Processing and Management 58 (2021) 102555

5. B. Sharchilev , M. Roizner , A. Rumyantsev , D. Ozornin , P. Serdyukov , M. de Rijke , "Web-based Startup Success Prediction" , CIKM 2018 , October 22 --26. Lingotto, Turin, Italy © Copyright held by the owner/author(s). ACM ISBN 123--4567.24-567/08/06 B. Sharchilev, M. Roizner, A. Rumyantsev, D. Ozornin, P. Serdyukov, M. de Rijke, "Web-based Startup Success Prediction", CIKM 2018, October 22--26. Lingotto, Turin, Italy © Copyright held by the owner/author(s). ACM ISBN 123--4567.24-567/08/06

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