VectorIndexer pyspark

from pyspark.ml import Pipeline
from pyspark.ml.regression import LinearRegression
from pyspark.ml.feature import VectorIndexer
from pyspark.ml.evaluation import RegressionEvaluator

# Automatically identify categorical features, and index them.
# We specify maxCategories so features with > 4 distinct values are treated as continuous.

featureIndexer = VectorIndexer(inputCol="features", \
                               outputCol="indexedFeatures",\
                               maxCategories=4).fit(transformed)

data = featureIndexer.transform(transformed)

Source: runawayhorse001.github.io

Similar codes

1 vote185 views1 answer
PyAudioAnalysis
Python
3 votes206 views1 answer
Best games made in pygame
Python
1 vote202 views2 answers
Os.execl
Python
0 vote201 views2 answers
Flask socket io
Python
0 vote255 views2 answers
How to import image in python
Python
0 vote279 views1 answer
Iterate over classes in module python
Python
5 votes248 views4 answers
Python print with 2 decimals
Python
14 votes186 views4 answers
Python lambda function if else
Python
46 votes201 views6 answers
Python try except print error
Python
0 vote188 views1 answer
Set permissions role discord.py
Python