What Makes a Good Feature? - Machine Learning Recipes #3

Опубликовано 27 апреля 2016, 16:56

Good features are informative, independent, and simple. Learn about these concepts using a histogram to visualize a feature from a toy dataset in Python in this episode of Machine Learning Recipes. John Gordon shares best practices for what a good feature is and best practices to follow.

Check out the playlist to watch the next episode in the series as we reinforce concepts, introduce clearer syntax, spend more time on testing, and continue building intuition for supervised learning.

Resources:
The code in this cast is similar to these great examples. You can use them to produce a more polished chart, if you like: goo.gle/47hDKIV

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Chapters:
0:00 - Intro
0:20 - Example of a good feature in binary classification
2:48 - Types of features to use
3:12 - Example of useless feature in binary classification
5:02 - In the next episode…

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And here's our playlist: goo.gl/KewA03

P.S: We realize some folks had dependency bugs with Graphviz (whoops!). Moving forward, this series won't use any libraries not already installed by Anaconda or Tensorflow.

Last: my code in this cast is similar to these great examples. You can use them to produce a more polished chart, if you like:

matplotlib.org/examples/statis...

Follow twitter.com/random_forests for updates on new episodes!