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 vote326 views1 answer
Markers seaborn
Python
12 votes339 views2 answers
Presskeys in python
Python
0 vote364 views1 answer
Leetcode matrix diagonal sum in python
Python
91 votes329 views6 answers
Create virtual environment python
Python
-1 vote363 views1 answer
How to enable matplotlib in notebook
Python
0 vote346 views1 answer
Copy model keras
Python
0 vote368 views1 answer
Tqdm for jupyter notebook
Python
0 vote365 views1 answer
Replace string if it contains a substring pandas
Python
0 vote321 views1 answer
Pandas separator are multiple spaces
Python
0 vote339 views1 answer
Count upper case characters in a string
Python