diff options
Diffstat (limited to 'python/pyspark/mllib/evaluation.py')
| -rw-r--r-- | python/pyspark/mllib/evaluation.py | 26 |
1 files changed, 14 insertions, 12 deletions
diff --git a/python/pyspark/mllib/evaluation.py b/python/pyspark/mllib/evaluation.py index aab5e5f4b7..c5cf3a4e7f 100644 --- a/python/pyspark/mllib/evaluation.py +++ b/python/pyspark/mllib/evaluation.py @@ -27,6 +27,8 @@ class BinaryClassificationMetrics(JavaModelWrapper): """ Evaluator for binary classification. + :param scoreAndLabels: an RDD of (score, label) pairs + >>> scoreAndLabels = sc.parallelize([ ... (0.1, 0.0), (0.1, 1.0), (0.4, 0.0), (0.6, 0.0), (0.6, 1.0), (0.6, 1.0), (0.8, 1.0)], 2) >>> metrics = BinaryClassificationMetrics(scoreAndLabels) @@ -38,9 +40,6 @@ class BinaryClassificationMetrics(JavaModelWrapper): """ def __init__(self, scoreAndLabels): - """ - :param scoreAndLabels: an RDD of (score, label) pairs - """ sc = scoreAndLabels.ctx sql_ctx = SQLContext(sc) df = sql_ctx.createDataFrame(scoreAndLabels, schema=StructType([ @@ -76,6 +75,9 @@ class RegressionMetrics(JavaModelWrapper): """ Evaluator for regression. + :param predictionAndObservations: an RDD of (prediction, + observation) pairs. + >>> predictionAndObservations = sc.parallelize([ ... (2.5, 3.0), (0.0, -0.5), (2.0, 2.0), (8.0, 7.0)]) >>> metrics = RegressionMetrics(predictionAndObservations) @@ -92,9 +94,6 @@ class RegressionMetrics(JavaModelWrapper): """ def __init__(self, predictionAndObservations): - """ - :param predictionAndObservations: an RDD of (prediction, observation) pairs. - """ sc = predictionAndObservations.ctx sql_ctx = SQLContext(sc) df = sql_ctx.createDataFrame(predictionAndObservations, schema=StructType([ @@ -148,6 +147,8 @@ class MulticlassMetrics(JavaModelWrapper): """ Evaluator for multiclass classification. + :param predictionAndLabels an RDD of (prediction, label) pairs. + >>> predictionAndLabels = sc.parallelize([(0.0, 0.0), (0.0, 1.0), (0.0, 0.0), ... (1.0, 0.0), (1.0, 1.0), (1.0, 1.0), (1.0, 1.0), (2.0, 2.0), (2.0, 0.0)]) >>> metrics = MulticlassMetrics(predictionAndLabels) @@ -176,9 +177,6 @@ class MulticlassMetrics(JavaModelWrapper): """ def __init__(self, predictionAndLabels): - """ - :param predictionAndLabels an RDD of (prediction, label) pairs. - """ sc = predictionAndLabels.ctx sql_ctx = SQLContext(sc) df = sql_ctx.createDataFrame(predictionAndLabels, schema=StructType([ @@ -277,6 +275,9 @@ class RankingMetrics(JavaModelWrapper): """ Evaluator for ranking algorithms. + :param predictionAndLabels: an RDD of (predicted ranking, + ground truth set) pairs. + >>> predictionAndLabels = sc.parallelize([ ... ([1, 6, 2, 7, 8, 3, 9, 10, 4, 5], [1, 2, 3, 4, 5]), ... ([4, 1, 5, 6, 2, 7, 3, 8, 9, 10], [1, 2, 3]), @@ -298,9 +299,6 @@ class RankingMetrics(JavaModelWrapper): """ def __init__(self, predictionAndLabels): - """ - :param predictionAndLabels: an RDD of (predicted ranking, ground truth set) pairs. - """ sc = predictionAndLabels.ctx sql_ctx = SQLContext(sc) df = sql_ctx.createDataFrame(predictionAndLabels, @@ -347,6 +345,10 @@ class MultilabelMetrics(JavaModelWrapper): """ Evaluator for multilabel classification. + :param predictionAndLabels: an RDD of (predictions, labels) pairs, + both are non-null Arrays, each with + unique elements. + >>> predictionAndLabels = sc.parallelize([([0.0, 1.0], [0.0, 2.0]), ([0.0, 2.0], [0.0, 1.0]), ... ([], [0.0]), ([2.0], [2.0]), ([2.0, 0.0], [2.0, 0.0]), ... ([0.0, 1.0, 2.0], [0.0, 1.0]), ([1.0], [1.0, 2.0])]) |