Description
Find the closest cluster center for every point.
Parameters
Name | Description | Type | Required? | Default Value |
---|---|---|---|---|
predictionDistanceCol | Column name of prediction. | String | ||
predictionCol | Column name of prediction. | String | ✓ | |
predictionDetailCol | Column name of prediction result, it will include detailed info. | String | ||
reservedCols | Names of the columns to be retained in the output table | String[] | null |
Script Example
Code
import numpy as np
import pandas as pd
data = np.array([
[0, "0 0 0"],
[1, "0.1,0.1,0.1"],
[2, "0.2,0.2,0.2"],
[3, "9 9 9"],
[4, "9.1 9.1 9.1"],
[5, "9.2 9.2 9.2"]
])
df = pd.DataFrame({"id": data[:, 0], "vec": data[:, 1]})
inOp1 = BatchOperator.fromDataframe(df, schemaStr='id int, vec string')
inOp2 = StreamOperator.fromDataframe(df, schemaStr='id int, vec string')
kmeans = KMeansTrainBatchOp().setVectorCol("vec").setK(2)
predictBatch = KMeansPredictBatchOp().setPredictionCol("pred")
kmeans.linkFrom(inOp1)
predictBatch.linkFrom(kmeans, inOp1)
[model,predict] = collectToDataframes(kmeans, predictBatch)
print(model)
print(predict)
predictStream = KMeansPredictStreamOp(kmeans).setPredictionCol("pred")
predictStream.linkFrom(inOp2)
predictStream.print(refreshInterval=-1)
StreamOperator.execute()
Results
Model
model_id model_info
0 0 {"vectorCol":"\"vec\"","latitudeCol":null,"lon...
1 1048576 {"clusterId":0,"weight":6.0,"vec":{"data":[9.0...
2 2097152 {"clusterId":1,"weight":6.0,"vec":{"data":[0.1...
Prediction
rowID id vec pred
0 0 0 0 0 1
1 1 0.1,0.1,0.1 1
2 2 0.2,0.2,0.2 1
3 3 9 9 9 0
4 4 9.1 9.1 9.1 0
5 5 9.2 9.2 9.2 0