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

2 votes335 views1 answer
Predicate
Python
0 vote299 views1 answer
Print e
Python
1 vote318 views1 answer
How to redirect to another page in django after login
Python
1 vote329 views1 answer
Seaborn plot set ylabel
Python
1 vote321 views2 answers
Python file basename
Python
0 vote323 views2 answers
Convert pandas dataframe to spark dataframe
Python
0 vote310 views1 answer
Convert string to object in python
Python
3 votes331 views2 answers
Extract one column from dataframe python
Python
4 votes322 views4 answers
Speech to write anything python code
Python
0 vote334 views1 answer
Yyyy-mm-dd hh:mm:ss.0 python
Python