What We Leave Behind Info

If your project is a on human legacy, deep features can quantify abstract concepts:

To build a deep feature using a tool like Featuretools, follow this workflow: What We Leave Behind

: Choose Aggregation primitives (calculating values across many related records, such as MEAN amount of data left behind) or Transform primitives (performing operations on a single table, such as YEAR from a timestamp). If your project is a on human legacy,

: By applying mathematical functions to time-series data, you can create features that predict how quickly certain "left behind" artifacts lose relevance or visibility. What We Leave Behind

: Run the DFS algorithm to output a new "feature matrix" containing these high-level, multi-layered insights. Applications for "What We Leave Behind"