"Several of these quantities are not provided in the data and therefore need to be imputed assumed. First, the valuation of the firm at t=2 in model time is defined as the latest associated with a “late-stage” round by the end of 2020. If no such rounds exist the company valuation is set to zero. If such a round exists but the valuation is provided by Pitchbook, I set it to zero. Next, Pitchbook typically provides the initial stake of the early stage investors. If it does not then I assume the early stake is Finally, I assume a constant dilution factor of .75."
I've made assumptions about the thing that effects what I try to predict the most and have found that my algorithm says people are wrong.
Sounds like those people that first learn about ML than immediately runs off to build a stock market predictor before inevitably learning about the investment worlds definition to "Data mining"
I've made assumptions about the thing that effects what I try to predict the most and have found that my algorithm says people are wrong.
Sounds like those people that first learn about ML than immediately runs off to build a stock market predictor before inevitably learning about the investment worlds definition to "Data mining"