A study in which machine-learning models were trained to assess over 1 million companies has shown that artificial intelligence (AI) can accurately determine whether a startup ﬁrm will fail or become successful.
“This research shows how ensembles of non-linear machine-learning models applied to big data have huge potential to map large feature sets to business outcomes, something that is unachievable with traditional linear regression models,” explains co-author Sanjiv Das, Professor of Finance and Data Science at Santa Clara University’s Leavey School of Business in the US.
The authors developed a novel ensemble of models in which the combined contribution of the models outweighs the predictive potential of each one alone.
Each model classiﬁes a company, placing it in one of several success categories or a failure category with a speciﬁc probability.
For example, a company might be very likely to succeed if the ensemble says it has a 75% probability of being in the IPO (listed on the stock exchange) or ‘acquired by another company’ category, while only 25% of its prediction would fall into the failed category.
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