16 min listen
[MINI] The Accuracy Paradox
FromData Skeptic
ratings:
Length:
17 minutes
Released:
Nov 27, 2015
Format:
Podcast episode
Description
Today's episode discusses the accuracy paradox. There are cases when one might prefer a less accurate model because it yields more predictive power or better captures the underlying causal factors describing the outcome variable you are interested in. This is especially relevant in machine learning when trying to predict rare events. We discuss how the accuracy paradox might apply if you were trying to predict the likelihood a person was a bird owner.
Released:
Nov 27, 2015
Format:
Podcast episode
Titles in the series (100)
[MINI] Noise!!: Our topic for this week is "noise" as in signal vs. noise. This is not a signal processing discussions, but rather a brief introduction to how the work noise is used to describe how much information in a dataset is useless (as opposed to... by Data Skeptic