although
LogisticRegressionModel, ReidgeRegressionModel,SVMModel etc has toPMML
method.
Can someone explain what is the issue here?
--
Thanks & Regards,
Fazlan Nazeem
*Software Engineer*
*WSO2 Inc*
Mobile : +94772338839
<%2B94%20%280%29%20773%20451194>
fazl...@wso2.com
ou should be able to call *
> *LinearRegressionModel#toPMML*
>
> On Thu, Oct 15, 2015 at 5:25 PM, Fazlan Nazeem wrote:
>
>> Hi
>>
>> I am trying to export a LinearRegressionModel in PMML format. According
>> to the following resource[1] PMML export is supported
Ok It turns out I was using the wrong LinearRegressionModel which was
in package
org.apache.spark.ml.regression;.
On Thu, Oct 15, 2015 at 3:23 PM, Fazlan Nazeem wrote:
> This is the API doc for LinearRegressionModel. It does not implement
> PMMLExportable
>
> https://spark.apa
d to add PMML export methods to the
> spark.ml API. I just made a JIRA for tracking that:
> https://issues.apache.org/jira/browse/SPARK-11171
>
> Joseph
>
> On Thu, Oct 15, 2015 at 2:58 AM, Fazlan Nazeem wrote:
>
>> Ok It turns out I was using the wrong LinearRegres
[adding dev]
On Wed, Nov 4, 2015 at 2:27 PM, Fazlan Nazeem wrote:
> I just went through all specifications, and they expect the version
> attribute. This should be addressed very soon because if we cannot use the
> PMML model without the version attribute, there is no use of gener
On Wed, Nov 4, 2015 at 11:42 AM, Fazlan Nazeem wrote:
> > [adding dev]
> >
> > On Wed, Nov 4, 2015 at 2:27 PM, Fazlan Nazeem wrote:
> >>
> >> I just went through all specifications, and they expect the version
> >> attribute. This should be addressed
t; Thanks,
> Vincenzo
>
> On Wed, Nov 4, 2015 at 12:14 PM, Fazlan Nazeem wrote:
>
>> Thanks Owen. Will do it
>>
>> On Wed, Nov 4, 2015 at 5:22 PM, Sean Owen wrote:
>>
>>> I'm pretty sure that attribute is required. I am not sure what PMML
>>> ver
score >=0 && label == 1) || (score <0 && label == 0))
>>>>{
>>>>return 1; //correct classiciation
>>>>}
>>>>else
>>>> return 0;
>>>>
>>>> }
>>>>}
>>>> );
>>>> // sum up all values in the rdd to get the number of correctly
>>>> classified examples
>>>> int sum=classification.reduce(new Function2>>> Integer>()
>>>> {
>>>> public Integer call(Integer arg0, Integer arg1)
>>>> throws Exception {
>>>> return arg0+arg1;
>>>> }});
>>>>
>>>> //compute accuracy as the percentage of the correctly classified
>>>> examples
>>>> double accuracy=((double)sum)/((double)classification.count());
>>>> System.out.println("Accuracy = " + accuracy);
>>>>
>>>> }
>>>> }
>>>> );
>>>> }
>>>> }
>>>>
>>>
>>>
>>>
>>> --
>>> Best Regards
>>>
>>> Jeff Zhang
>>>
>>
>>
>
>
> --
> Best Regards
>
> Jeff Zhang
>
--
Thanks & Regards,
Fazlan Nazeem
*Software Engineer*
*WSO2 Inc*
Mobile : +94772338839
<%2B94%20%280%29%20773%20451194>
fazl...@wso2.com
