Learning Curve¶
Generates a learning curve by training model multiple timeson incrementally larger subsets of the data and using cross validation for scoring. Plot performance of train-mean vs. test-mean for curve.
Documentation¶
Definition¶
- Input ports:
- model
model
Model
- X
table
X
- Y
table
Y
- Output ports:
- results
table
results
- statistics
table
statistics
- Configuration:
- Shuffle (shuffle)
Randomizes the input dataset before passed to internal cross validation
- Smallest fraction (smallest)
Size of the smallest dataset as fraction of total
- Steps (steps)
Number of different sizes of training/test data measured
- Cross validation folds (cv)
Number of fold of cross-validation (minimum 2)
Some of the docstrings for this module have been automatically extracted from the scikit-learn library and are covered by their respective licenses.
