The error message “TypeError: Cannot convert type <class ‘pyspark.ml.linalg.DenseVector’> into Vector” usually occurs when you are trying to use an instance of pyspark.ml.linalg.DenseVector in a place where PySpark is expecting an instance of pyspark.mllib.linalg.Vector.
This error occurs because pyspark.ml.linalg.DenseVector and pyspark.mllib.linalg.Vector are two different vector classes in PySpark and are not interchangeable. pyspark.ml.linalg.DenseVector is a newer vector class introduced in PySpark version 2.0, whereas pyspark.mllib.linalg.Vector is an older vector class that was used in earlier versions of PySpark.
To resolve this error, you can convert the pyspark.ml.linalg.DenseVector instance to a pyspark.mllib.linalg.Vector instance before using it in the code that is causing the error. You can do this using the fromML() method provided by the pyspark.ml.linalg.DenseVector class.
Here’s an example of how to convert a pyspark.ml.linalg.DenseVector instance to a pyspark.mllib.linalg.Vector instance:
from pyspark.ml.linalg import DenseVector
from pyspark.mllib.linalg import Vectors
# Create a DenseVector instance
dense_vector = DenseVector([1.0, 2.0, 3.0])
# Convert the DenseVector instance to a Vector instance
vector = Vectors.fromML(dense_vector)
# Now you can use the Vector instance wherever PySpark expects a Vector
In this example, we first create a pyspark.ml.linalg.DenseVector instance called dense_vector. We then convert it to a pyspark.mllib.linalg.Vector instance called vector using the fromML() method provided by the pyspark.ml.linalg.DenseVector class. Finally, we can use the vector instance wherever PySpark expects a pyspark.mllib.linalg.Vector instance.
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