zhengruifeng commented on a change in pull request #27519: [SPARK-30770][ML]
avoid vector conversion in GMM.transform
URL: https://github.com/apache/spark/pull/27519#discussion_r386236966
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File path: python/pyspark/ml/clustering.py
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@@ -270,19 +270,16 @@ class GaussianMixture(JavaEstimator,
_GaussianMixtureParams, JavaMLWritable, Jav
3
>>> gaussians[0].mean
DenseVector([0.825, 0.8675])
- >>> gaussians[0].cov.toArray()
- array([[ 0.005625 , -0.0050625 ],
- [-0.0050625 , 0.00455625]])
+ >>> gaussians[0].cov
+ DenseMatrix(2, 2, [0.0056, -0.0051, -0.0051, 0.0046], 0)
>>> gaussians[1].mean
- DenseVector([-0.4777, -0.4096])
- >>> gaussians[1].cov.toArray()
- array([[ 0.1679695 , 0.13181786],
- [ 0.13181786, 0.10524592]])
+ DenseVector([-0.87, -0.72])
+ >>> gaussians[1].cov
+ DenseMatrix(2, 2, [0.0016, 0.0016, 0.0016, 0.0016], 0)
>>> gaussians[2].mean
- DenseVector([-0.4473, -0.3853])
- >>> gaussians[2].cov.toArray()
- array([[ 0.16730412, 0.13112435],
- [ 0.13112435, 0.10469614]])
+ DenseVector([-0.055, -0.075])
+ >>> gaussians[2].cov
+ DenseMatrix(2, 2, [0.002, -0.0011, -0.0011, 0.0006], 0)
Review comment:
Since the maxIter was changed from 10 to 30, the model coefficients are
different.
I had checked the model coefficients of both master and this PR with
maxIter=30, they are the same. But they are different from coefficients at
iteration=10;
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