diff options
Diffstat (limited to 'examples/src/main/python/mllib/decision_tree_runner.py')
-rwxr-xr-x | examples/src/main/python/mllib/decision_tree_runner.py | 17 |
1 files changed, 10 insertions, 7 deletions
diff --git a/examples/src/main/python/mllib/decision_tree_runner.py b/examples/src/main/python/mllib/decision_tree_runner.py index 61ea4e06ec..fccabd841b 100755 --- a/examples/src/main/python/mllib/decision_tree_runner.py +++ b/examples/src/main/python/mllib/decision_tree_runner.py @@ -106,8 +106,7 @@ def reindexClassLabels(data): def usage(): print >> sys.stderr, \ - "Usage: decision_tree_runner [libsvm format data filepath]\n" + \ - " Note: This only supports binary classification." + "Usage: decision_tree_runner [libsvm format data filepath]" exit(1) @@ -127,16 +126,20 @@ if __name__ == "__main__": # Re-index class labels if needed. (reindexedData, origToNewLabels) = reindexClassLabels(points) + numClasses = len(origToNewLabels) # Train a classifier. categoricalFeaturesInfo = {} # no categorical features - model = DecisionTree.trainClassifier(reindexedData, numClasses=2, + model = DecisionTree.trainClassifier(reindexedData, numClasses=numClasses, categoricalFeaturesInfo=categoricalFeaturesInfo) # Print learned tree and stats. print "Trained DecisionTree for classification:" - print " Model numNodes: %d\n" % model.numNodes() - print " Model depth: %d\n" % model.depth() - print " Training accuracy: %g\n" % getAccuracy(model, reindexedData) - print model + print " Model numNodes: %d" % model.numNodes() + print " Model depth: %d" % model.depth() + print " Training accuracy: %g" % getAccuracy(model, reindexedData) + if model.numNodes() < 20: + print model.toDebugString() + else: + print model sc.stop() |