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Getting Individual Metrics From H2O Model in Python [Code Snippets]

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Getting Individual Metrics From H2O Model in Python [Code Snippets]

Learn about creating a test data frame to run the H2O deep learning algorithm and collecting individual model metrics based on training and/or validation data.

· AI Zone ·
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Start coding something amazing with the IBM library of open source AI code patterns.  Content provided by IBM.

You can get individual model metrics for your model based on training and/or validation data. Here is the code snippets.

Below, I am creating a test data frame to run the H2O deep learning algorithm and then showing how to collect individual model metrics based on training and/or validation data.

import h2o
h2o.init(strict_version_check= False , port = 54345)
from h2o.estimators.deeplearning import H2ODeepLearningEstimator
model = H2ODeepLearningEstimator()
rows = [[1,2,3,4,0], [2,1,2,4,1], [2,1,4,2,1], [0,1,2,34,1], [2,3,4,1,0]] * 50
fr = h2o.H2OFrame(rows)
X = fr.col_names[0:4]

## Classification Model
fr[4] = fr[4].asfactor()
model.train(x=X, y="C5", training_frame=fr)
print('Model Type:', model.type)
print('logloss', model.logloss(valid = False))
print('Accuracy', model.accuracy(valid = False))
print('AUC', model.auc(valid = False))
print('R2', model.r2(valid = False))
print('RMSE', model.rmse(valid = False))
print('Error', model.error(valid = False))
print('MCC', model.mcc(valid = False))

## Regression Model
fr = h2o.H2OFrame(rows)
model.train(x=X, y="C5", training_frame=fr)
print('Model Type:', model.type)
print('R2', model.r2(valid = False))
print('RMSE', model.rmse(valid = False))

Note: As I did not pass the validation frame, I set valid = False to get training metrics. If you have passed validation metrics then you can set valid = True to get validation metrics as well.

If you want to see what is inside model object, you can look at the JSON object below:

model.get_params()

That's it. Enjoy!

Start coding something amazing with the IBM library of open source AI code patterns.  Content provided by IBM.

Topics:
metrics ,h2o ,python ,ai ,deep learning ,algorithm ,data analytics

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