1.5 has not yet been released; what is the commit hash that you are building?

On Wed, Aug 5, 2015 at 10:29 AM, Hayri Volkan Agun <volkanagun@gmail.com> wrote:
Hi,

In Spark 1.5 I saw a result for precision 1.0 and recall 0.01 for decision tree classification.
While precision a hundred the recall shouldn't be so small...I checked the code, everything seems ok
but why I got such a result is unexplainable. As far as I understand from scala code the row sum is the actual
class counts, the column sum is predictions sum am I right? 
I am doing additional tests for comparison with my own code...
I attached a document for my reuters tests on page 3.


On Wed, Aug 5, 2015 at 7:57 PM, Feynman Liang <fliang@databricks.com> wrote:
Also, what version of Spark are you using?

On Wed, Aug 5, 2015 at 9:57 AM, Feynman Liang <fliang@databricks.com> wrote:
Hi Hayri,

Can you provide a sample of the expected and actual results?

Feynman

On Wed, Aug 5, 2015 at 6:19 AM, Hayri Volkan Agun <volkanagun@gmail.com> wrote:
The results in MulticlassMetrics is totally wrong. They are improperly calculated.
Confusion matrix may be true I don't know but for each label scores are wrong.

--
Hayri Volkan Agun
PhD. Student - Anadolu University





--
Hayri Volkan Agun
PhD. Student - Anadolu University