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Create a sparse vector, using either a dictionary, a list of (index, value) pairs, or two separate arrays of indices and values (sorted by index). Parameters. sizeint. Size of the vector. args. Non-zero entries, as a dictionary, list of tuples, or two sorted lists containing indices and values. Examples.
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VectorAssembler — PySpark 3.1.1 documentation. VectorAssembler ¶. class pyspark.ml.feature.VectorAssembler(*, inputCols=None, outputCol=None, handleInvalid='error') [source] ¶. A feature transformer that merges multiple columns into a vector column. New in version 1.4.0. Examples.
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21 de jul. de 2015 · While a dense vector is when most of the values in the vector are non zero. If you have to create a sparse vector from the dense vector you specified, use the following syntax: import org.apache.spark.mllib.linalg.Vector; import org.apache.spark.mllib.linalg.Vectors; Vector sparseVector = Vectors.sparse(4, new int[] {1, 3}, new ...
