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

41 votes111 views6 answers
Dataframe in python
Python
2 votes109 views1 answer
Pygame get screen width and height
Python
0 vote114 views1 answer
Reset button combobocx tkinter
Python
14 votes106 views6 answers
Flask setup
Python
1 vote95 views1 answer
Str replace python regex
Python
0 vote110 views1 answer
Super().__init__(pos, model) in python
Python
10 votes120 views3 answers
Text recognition python library
Python
14 votes97 views2 answers
String slice
Python
5 votes94 views3 answers
How to calculate mean in python
Python
0 vote95 views1 answer
Count number of subdirectories
Python