Comment Comment by anton_tarasenko 0. I measure Show HN projects, some of which are startups. The dead/alive status as success is a proper measure for survival. For success, see the section on commercial success.1. OLS works fine in classification problems. And it has advantages. For example, see http://chrisblattman.com/2015/07/22/statistician-neal-beck-j...And I purposefully included results from three models, not one. They all say the same thing.2. Multicollinearity refers to perfect multicollinearity. Having correlated independent variables (as in score and comments) are okay. See http://stats.stackexchange.com/questions/86269/what-is-the-e...3. I mention R² as one measure of predictive power.4. The regressions without GitHub-hosted projects return same results. parent anton_tarasenko 10 years ago
1. OLS works fine in classification problems. And it has advantages. For example, see http://chrisblattman.com/2015/07/22/statistician-neal-beck-j...
And I purposefully included results from three models, not one. They all say the same thing.
2. Multicollinearity refers to perfect multicollinearity. Having correlated independent variables (as in score and comments) are okay. See http://stats.stackexchange.com/questions/86269/what-is-the-e...
3. I mention R² as one measure of predictive power.
4. The regressions without GitHub-hosted projects return same results.