changing the first / primary / conversion event in eventNames changes what the
algorithm will predict. CCO can predict anything in the data by changing this
conversion events to the one you want.
However that means that you must have good data for the primary/conversion
event. Removing it will
I have a model deployed for this app, it works if I keep only (facet,
search) as event types. When asking for a prediction to my deployed model I
have an answer in relation with my data (about cars). I checked that the
data is sent at the right accesskey in the right ES index. This part is
fine I
Also what version of UR you're into? Is it the latest one? I've only worked
with UR 0.50 .
On Wed, Jun 7, 2017 at 3:12 PM, Vaghawan Ojha wrote:
> Yes you need to build the app again when you change something in the
> engine.json. That is every time when you change
Yes the three event types that I defined in the engine.json exist in my
dataset, facet is my primary, I checked that it exists.
I think it is not needed to build again when changing something in the
engine.json, as the file is read in the process but I built it and tried
again and I still have
Hi,
For me this problem had happened when I had mistaken my primary events. The
first eventName in the eventName array "eventNames":
["facet","view","search"] is primary. There is that event in your data.
Did you make sure, you built the app again when you changed the eventName
in engine.json?
You could explicitly do
pio train -- --master spark://localhost:7077 --driver-memory 16G
--executor-memory 24G
and change the spark master url and the memories configuration. And see if
that works.
Thanks
On Wed, Jun 7, 2017 at 1:55 PM, Bruno LEBON wrote:
> Hi,
>
> Using
Hi,
Using UR with PIO 0.10 I am trying to train my dataset. In return I get the
following error:
*...*
*[INFO] [DataSource] Received events List(facet, view, search)*
*[INFO] [DataSource] Number of events List(5, 4, 6)*
*[INFO] [Engine$] org.template.TrainingData does not support data sanity