text: # _*_ coding:utf-8 _*_
  
  '''
  LogisticRegression
  '''
  
  from pyspark.sql import SparkSession
  from pyspark.ml.classification import LogisticRegression
  
  spark = SparkSession.builder.appName("LogisticRegression").getOrCreate()
  
  paths="/export/home/ry/spark-2.2.1-bin-hadoop2.7/data/mllib/"
  
  # Load training data
  
  training=spark.read.format("libsvm").load(paths+"sample_libsvm_data.txt")
  
  lr=LogisticRegression(maxIter=10,regParam=0.3,elasticNetParam=0.8)
  
  # Fit the model
  
  lrModel=lr.fit(training)
  
  # print the coefficients and intercept for logistic regression
  
  print("Coefficients: "+str(lrModel.coefficients))
  print("Intercept: "+str(lrModel.intercept))
  