Version 1
: Received: 3 January 2024 / Approved: 4 January 2024 / Online: 4 January 2024 (09:00:44 CET)
How to cite:
Bhattacharya, D. Utilizing Base Machine Learning Models to Determine Key Factors of Success on an Indian Tech Startup. Preprints2024, 2024010368. https://doi.org/10.20944/preprints202401.0368.v1
Bhattacharya, D. Utilizing Base Machine Learning Models to Determine Key Factors of Success on an Indian Tech Startup. Preprints 2024, 2024010368. https://doi.org/10.20944/preprints202401.0368.v1
Bhattacharya, D. Utilizing Base Machine Learning Models to Determine Key Factors of Success on an Indian Tech Startup. Preprints2024, 2024010368. https://doi.org/10.20944/preprints202401.0368.v1
APA Style
Bhattacharya, D. (2024). Utilizing Base Machine Learning Models to Determine Key Factors of Success on an Indian Tech Startup. Preprints. https://doi.org/10.20944/preprints202401.0368.v1
Chicago/Turabian Style
Bhattacharya, D. 2024 "Utilizing Base Machine Learning Models to Determine Key Factors of Success on an Indian Tech Startup" Preprints. https://doi.org/10.20944/preprints202401.0368.v1
Abstract
Startups are playing increasingly influential roles in the technology sector of the world. India has been a rapidly growing economy and hosts over one hundred thousand total startups. Investors have been increasingly investing in the Indian technology sector. However, the Indian startup ecosystem is different to the American startup ecosystem and requires a separate analysis to determine important influences for their success. Through this research with responsible machine learning, entrepreneurs will be empowered to better understand how to successfully raise their company. I collected data from Crunchbase and defined a successful startup as one who has acquired another company, was acquired, or went public. I used Random Forest, XGBoost, LightGBM, and CatBoost to predict the success of the startups. To determine the most important factors, I used the feature importance tools provided by the models. I compared these results and found that the time taken between the founding and first funding of the company, commonly referred to as seed lag, was the most pivotal factor to every model’s prediction of success.
Keywords
machine learning; startups; indian tech industry; responsible ai
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
