title: How to set seed or what we can do to make intercept constant in linear regression?
body: <p>I am creating a linear regression model in pyspark. but each time it give different intercept and weights . How to make constant ? I have used random.seed() but it is not working ? Anyone have any idea how to make constant intercept and weights in pyspark? Please give syntax or way how to handle this ?
  I am using spark 1.4.2 and python 2.7 version.      </p>
  
  <pre class="lang-python prettyprint-override"><code>from pyspark.ml.regression import LinearRegression 
  from pyspark.sql.types import *
  seed = 42
  train_df, test_df = miles_new_df.randomSplit( [0.7, 0.3], seed = seed )
  linreg = LinearRegression(maxIter=500,regParam=0.0) #modelparameters
  lm = linreg.fit( train_df )  #fitting
  lm.intercept
  lm.weights
  </code></pre>