public final class KmeansPlusPlusInitialization extends PrimitiveOp implements Operand<Float>
Rows of points are assumed to be input points. One row is selected at random. Subsequent rows are sampled with probability proportional to the squared L2 distance from the nearest row selected thus far till num_to_sample rows have been sampled.
operation
Modifier and Type | Method and Description |
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Output<Float> |
asOutput()
Returns the symbolic handle of a tensor.
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static KmeansPlusPlusInitialization |
create(Scope scope,
Operand<Float> points,
Operand<Long> numToSample,
Operand<Long> seed,
Operand<Long> numRetriesPerSample)
Factory method to create a class wrapping a new KmeansPlusPlusInitialization operation.
|
Output<Float> |
samples()
Matrix of shape (num_to_sample, d).
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equals, hashCode, op, toString
public static KmeansPlusPlusInitialization create(Scope scope, Operand<Float> points, Operand<Long> numToSample, Operand<Long> seed, Operand<Long> numRetriesPerSample)
scope
- current scopepoints
- Matrix of shape (n, d). Rows are assumed to be input points.numToSample
- Scalar. The number of rows to sample. This value must not be larger than n.seed
- Scalar. Seed for initializing the random number generator.numRetriesPerSample
- Scalar. For each row that is sampled, this parameter
specifies the number of additional points to draw from the current
distribution before selecting the best. If a negative value is specified, a
heuristic is used to sample O(log(num_to_sample)) additional points.public Output<Float> asOutput()
Operand
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
asOutput
in interface Operand<Float>
OperationBuilder.addInput(Output)
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