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

9 votes206 views6 answers
What is enumerate in python
Python
1 vote213 views1 answer
How to print the text of varying length in python
Python
1 vote196 views1 answer
Print console sys.stdout
Python
1 vote185 views2 answers
Python detect internet connection
Python
0 vote192 views1 answer
Recursive python program to print numbers from n to 1
Python
0 vote145 views1 answer
Left rotation in list
Python
0 vote208 views1 answer
Webview_flutter
Python
0 vote184 views1 answer
UnicodeDecodeError: 'cp950' codec can't decode byte 0xe3 in position 70: illegal multibyte sequence
Python
1 vote189 views1 answer
Tuple comprehension python
Python
1 vote200 views1 answer
Python hide input
Python