Hello, I believe there is a mismatch between the API documentation (1.5.2) and the software currently available.
Not all functions mentioned here http://spark.apache.org/docs/latest/api/python/pyspark.ml.html#module-pyspark.ml.recommendation are, in fact available. For example, the code below from the tutorial works # Build the recommendation model using Alternating Least Squares rank = 10 numIterations = 10 model = ALS.train(ratings, rank, numIterations) While the alternative shown in the API documentation will not (it will complain that ALS takes no arguments. Also, but inspecting the module with Python utilities I could not find several methods mentioned in the API docs) >>> df = sqlContext.createDataFrame( ... [(0, 0, 4.0), (0, 1, 2.0), (1, 1, 3.0), (1, 2, 4.0), (2, 1, 1.0), (2, 2, 5.0)], ... ["user", "item", "rating"]) >>> als = ALS(rank=10, maxIter=5) >>> model = als.fit(df) Thank you,
