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Om Shanti Om 2007 Hindi 720P BRRip X264 E SuB 27golkes

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Downloadhttps://bytlly.com/2m3jng

 

 

Downloadhttps://bytlly.com/2m3jng

 

 

 

 

 

 

 

 

Om Shanti Om 2007 Hindi 720P BRRip X264 E SuB 27golkes

 

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Forgive me friends, but I could not resist sharing these two wonderful sets of images of Om Shanti Om from the film. Will probably come back to post more during the film’s release.
�Now a days VCDs and DVDs are no longer available in the market.�
Download E-pub e-book for free.Q:

Classifying an object by its features in MLlib

I’m working on a new classification problem where there are lots of different features to decide on for the different objects that the system is to decide between (the system gets a bunch of images as input, and each image may have different sets of features).
I’d like to use MLlib to do the actual classification, but my code isn’t working as I expect. Here’s my code:
val df = df.map(r => LabeledPoint(r._1, r._2.asML)
val dataloader = new FileInputDStream(path, 1, true, new Configuration())
val transformers = new JavaSequentialFeatureTransformers(dataset)
val classifier = new LinearSVC()
val model = classifier.train(transformers, df)

I am setting the training as a linear SVM, but if I change this to a linear LSVM, I get the following error:

Exception in thread “main” java.lang.IllegalArgumentException:
featureVectors must not be null.

I’ve looked at the code for the JavaSequentialFeatureTransformers and it appears to be using JavaCoordinateClassifier which requires that featureVectors be null.
How should I be setting this up in the way that it will work correctly?

A:

The documentation for JavaSequentialFeatureTransformers states:

Prerequisite: featureVectors must not be null

It looks like you can get around this using a more advanced version of a SequentialFeatureTransformers. The following works for me:
import org.apache.spark.ml.feature.Extractors
import org.apache.spark.ml.feature.LabeledPoint
import org.apache.spark.mllib.classification.{LinearSVC, LogisticRegression}
import org.apache.spark.mllib.linalg.{Vector, VectorUDT}
import org.apache
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