Timeline for What is the best algorithm/solution for predicting the following?
Current License: CC BY-SA 4.0
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| May 2, 2019 at 6:34 | comment | added | free_road | The issue I see with trees, is that there is a decision made about a particular attribute of the data which distinguishes it as either one thing, or the other. All the variables I'm working with are standardized - so, yes, I can work with the variance, and certainly I'll adjust to work with individual-level data rather than country-level, however the issue remains: None of these variablesby itself is indicative enough of a certain country. The best we can do is state its proximity to a country's average in terms of standard deviation. And, like you said, variance is often very large. | |
| May 1, 2019 at 2:56 | history | edited | Juan Esteban de la Calle | CC BY-SA 4.0 |
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| May 1, 2019 at 2:07 | comment | added | m13op22 | Would also like to add that it could be helpful, if not being done already, to convert the categorical target variable into dummy variables (column names are the categories, values are 0 or 1) | |
| Apr 30, 2019 at 19:25 | history | answered | Juan Esteban de la Calle | CC BY-SA 4.0 |