Learning Curves
The following code cell produces four graphs for a decision tree model with different maximum depths. Each graph visualizes the learning curves of the model for both training and testing as the size of the training set is increased. Note that the shaded region of a learning curve denotes the uncertainty of that curve (measured as the standard deviation). The model is scored on both the training and testing sets using R2, the coefficient of determination.
Run the code cell below and use these graphs to answer the following question.
In [6]:
Produce learning curves for varying training set sizes and maximum depths
vs.ModelLearning(features, prices)
NameError Traceback (most recent call last)
in ()
1 # Produce learning curves for varying training set sizes and maximum depths
----> 2 vs.ModelLearning(features, prices)
NameError: name 'vs' is not defined
Why is asking me to define "vs"? The graphs are not running
Learning Curves The following code cell produces four graphs for a decision tree model with different maximum depths. Each graph visualizes the learning curves of the model for both training and testing as the size of the training set is increased. Note that the shaded region of a learning curve denotes the uncertainty of that curve (measured as the standard deviation). The model is scored on both the training and testing sets using R2, the coefficient of determination.
Run the code cell below and use these graphs to answer the following question.
In [6]:
Produce learning curves for varying training set sizes and maximum depths
vs.ModelLearning(features, prices)
NameError Traceback (most recent call last)