Re: Does DecisionTree model in MLlib deal with missing values?

On Sun, Jan 11, 2015 at 9:46 PM, Christopher Thom christopher.t...@quantium.com.au wrote: Is there any plan to extend the data types that would be accepted by the Tree models in Spark? e.g. Many models that we build contain a large number of string-based categorical factors. Currently the

Re: Does DecisionTree model in MLlib deal with missing values?

requires double data type, in this case what can I do? Thank you very much. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Does-DecisionTree-model-in-MLlib-deal-with-missing-values-tp21080.html Sent from the Apache Spark User List mailing list archive

RE: Does DecisionTree model in MLlib deal with missing values?

10:53 PM To: Carter Cc: user@spark.apache.org Subject: Re: Does DecisionTree model in MLlib deal with missing values? I do not recall seeing support for missing values. Categorical values are encoded as 0.0, 1.0, 2.0, ... When training the model you indicate which are interpreted as categorical

Does DecisionTree model in MLlib deal with missing values?

. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Does-DecisionTree-model-in-MLlib-deal-with-missing-values-tp21080.html Sent from the Apache Spark User List mailing list archive at Nabble.com