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Diffstat (limited to 'docs/mllib-clustering.md')
| -rw-r--r-- | docs/mllib-clustering.md | 6 |
1 files changed, 1 insertions, 5 deletions
diff --git a/docs/mllib-clustering.md b/docs/mllib-clustering.md index 93cd0c1c61..d0be032868 100644 --- a/docs/mllib-clustering.md +++ b/docs/mllib-clustering.md @@ -152,11 +152,7 @@ clusters = KMeans.train(parsedData, 2, maxIterations=10, runs=10, initializationMode="random") # Evaluate clustering by computing Within Set Sum of Squared Errors -def error(point): - center = clusters.centers[clusters.predict(point)] - return sqrt(sum([x**2 for x in (point - center)])) - -WSSSE = parsedData.map(lambda point: error(point)).reduce(lambda x, y: x + y) +WSSSE = clusters.computeCost(parsedData) print("Within Set Sum of Squared Error = " + str(WSSSE)) # Save and load model |