Understanding Confusion Matrices

Eli Bendersky explains what it is a confusion matrix tells us:

Now comes our first batch of definitions.

  • True positive (TP): Positive test result matches reality — the person is actually sick and tested positive.
  • False positive (FP): Positive test result doesn’t match reality — the test is positive but the person is not actually sick.
  • True negative (TN): Negative test result matches reality — the person is not sick and tested negative.
  • False negative (FN): Negative test result doesn’t match reality — the test is negative but the person is actually sick.

Folks get confused with these often, so here’s a useful heuristic: positive vs. negative reflects the test outcome; true vs. false reflects whether the test got it right or got it wrong.

It’s a nice read.  The next step, after understanding these, is figuring out in which circumstances we want to weigh some of these measures more than others.

Related Posts

Testing Spatial Equilibrium Concepts With tidycensus

Ignacio Sarmiento Barbieri walks us through the concept of spatial equilibrium and tests using data from the tidycensus package: Let’s take the model to the data and reproduce figures 2.1. and 2.2 of “Cities, Agglomeration, and Spatial Equilibrium”. The focus are two cities, Chicago and Boston. These cities are chosen because both differ in how easy […]

Read More

Interacting With SQL Server From Pandas

Tomaz Kastrun shows how to use pyodbc to interact with a SQL Server database from Pandas: In the SQL Server Management Studio (SSMS), the ease of using external procedure sp_execute_external_script has been (and still will be) discussed many times. But the reason for this short blog post is the fact that, changing Python environments using Conda package/module management within Microsoft […]

Read More

Categories

March 2018
MTWTFSS
« Feb Apr »
 1234
567891011
12131415161718
19202122232425
262728293031