title: How to determine Preference/Confidence in ALS.transImplicit in Spark?
body: <p>I am using <code>trainsimplicit</code> from <code>ALS</code> in Spark.
   From the documentation page: <a href="http://spark.apache.org/docs/latest/api/python/pyspark.mllib.html#pyspark.mllib.recommendation.ALS.trainImplicit" rel="nofollow">http://spark.apache.org/docs/latest/api/python/pyspark.mllib.html#pyspark.mllib.recommendation.ALS.trainImplicit</a>, use <code>trainImplicit(ratings, rank, iterations=5, lambda_=0.01, blocks=-1, alpha=0.01, nonnegative=False, seed=None)</code> to train a model.</p>
  
  <p>My question is should we input <code>ratings</code> as <code>(user, product, view times/watching time &gt;0)</code>?
  or <code>(user, product, preference = 0/1)</code>?</p>
  
  <p>Meanwhile, I noticed if <code>alpha =0.01</code> is changed to other values, the results will be different. How can we know which the preference-confidence relation, like <code>c = 1 + alpha * r</code> or <code>1+ alpha * log(1+r/e)</code> (<code>r</code> could be time duration or number of frequency) is used in Spark during training?</p>
  
  <p>I also noticed, in the web <a href="https://spark.apache.org/docs/1.4.0/api/python/_modules/pyspark/mllib/recommendation.html#ALS.trainImplicit" rel="nofollow">https://spark.apache.org/docs/1.4.0/api/python/_modules/pyspark/mllib/recommendation.html#ALS.trainImplicit</a>, there is <code>cls</code> in the <code>trainsimplicit</code> classmethod. Is it a way to define the preference-confidence relation?</p>
  
  <p>A ton of thanks!</p>