Created
August 10, 2016 18:37
-
-
Save anonymous/06879824c2a1c6ce29184c28ff3daf03 to your computer and use it in GitHub Desktop.
results of GraphLab's machine learning process
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
SUCCESS: Optimal solution found. | |
PROGRESS: Model selection based on validation accuracy: | |
PROGRESS: --------------------------------------------- | |
PROGRESS: BoostedTreesClassifier : 0.833333313465 | |
PROGRESS: RandomForestClassifier : 0.833333313465 | |
PROGRESS: DecisionTreeClassifier : 0.833333313465 | |
PROGRESS: LogisticClassifier : 0.833333 | |
PROGRESS: --------------------------------------------- | |
PROGRESS: Selecting BoostedTreesClassifier based on validation set performance. | |
>>> predictions = model.classify(test_data) | |
>>> results = model.evaluate(test_data) | |
>>> results | |
{'f1_score': 0.9679633867276888, 'auc': 0.9955012077294686, 'recall': 0.9722222222222222, 'precision': 0.9666666666666667, 'log_loss': 0.16391208595710882, 'roc_curve': Columns: | |
threshold float | |
fpr float | |
tpr float | |
p int | |
n int | |
class int | |
Rows: 300003 | |
Data: | |
+-----------+-----+-----+----+----+-------+ | |
| threshold | fpr | tpr | p | n | class | | |
+-----------+-----+-----+----+----+-------+ | |
| 0.0 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 1e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 2e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 3e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 4e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 5e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 6e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 7e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 8e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
| 9e-05 | 1.0 | 1.0 | 11 | 21 | 0 | | |
+-----------+-----+-----+----+----+-------+ | |
[300003 rows x 6 columns] | |
Note: Only the head of the SFrame is printed. | |
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns., 'confusion_matrix': Columns: | |
target_label str | |
predicted_label str | |
count int | |
Rows: 4 | |
Data: | |
+-----------------+-----------------+-------+ | |
| target_label | predicted_label | count | | |
+-----------------+-----------------+-------+ | |
| Iris-setosa | Iris-setosa | 11 | | |
| Iris-versicolor | Iris-versicolor | 11 | | |
| Iris-versicolor | Iris-virginica | 1 | | |
| Iris-virginica | Iris-virginica | 9 | | |
+-----------------+-----------------+-------+ | |
[4 rows x 3 columns] | |
, 'accuracy': 0.96875} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment