Error Table Across Two Data Distributions and Three Error Types
An error table for the cat image detector can put two data distributions on the x-axis and three error types on the y-axis: human-level error, error on examples the algorithm has trained on, and error on examples the algorithm has not trained on. Filling additional entries may sometimes give additional insight about what the algorithm is doing on the two data distributions.
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Machine Learning
Deep Learning
Supervised Learning
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Data Science
Machine Learning Strategy
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Error Table Across Two Data Distributions and Three Error Types
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Learn After
In the error table for the cat image detector, what is placed along the x-axis?
The error table for the cat image detector places three data distributions along the x-axis.
The error table places two data _____ on the x-axis and three error types on the y-axis.
Match each axis or row label in the error table to its role in the cat image detector example.
Order the steps for constructing the error table described in Machine Learning Yearning.
What does Andrew Ng say is a benefit of filling in additional entries in the error table?
Andrew Ng states that drawing errors as table entries makes it easier to understand how different error types relate to each other.
One y-axis row in the error table is 'error on examples the algorithm has _____ on.'
Match each error table comparison to the diagnostic insight it reveals about the algorithm.
Order the reasoning steps for diagnosing algorithm behavior using the completed error table.