azagrebin commented on a change in pull request #6425: [FLINK-9664][Doc] fixing documentation in ML quick start URL: https://github.com/apache/flink/pull/6425#discussion_r208576999
########## File path: docs/dev/libs/ml/quickstart.md ########## @@ -129,6 +129,10 @@ and the [test set here](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/b This is an astroparticle binary classification dataset, used by Hsu et al. [[3]](#hsu) in their practical Support Vector Machine (SVM) guide. It contains 4 numerical features, and the class label. +Before importing the traning and test dataset, Flink SVM only supports threshold binary values of +`+1.0` and `-1.0`. Thus a conversion is needed upon downloading the svmguide1 dataset since it is +labelled using `1`s and `0`s. + Review comment: I think this section belongs to the beginning of the next one `Classification`, because it is about LibSVM format. The code example of conversion could be also provided to make the example fully 'copy-paste' runnable. Small thing is also typo in `traning` -> `training`. I would suggest to modify the code example in this `LibSVM files` section like this: ``` val astroTrainLibSVM: DataSet[LabeledVector] = MLUtils.readLibSVM(env, "/path/to/svmguide1") val astroTestLibSVM: DataSet[LabeledVector] = MLUtils.readLibSVM(env, "/path/to/svmguide1.t") ``` to have no SVM training specifics here, and add something like this to the beginning of `Classification` section: _... After importing the training and test dataset, the data needs to be prepared for the classification, because Flink SVM only supports ... conversion is needed after downloading ..._ And then the code example: ``` def svmNormaliser : LabeledVector => LabeledVector = lv => LabeledVector(if (lv.label > 0.0) 1.0 else -1.0, lv.vector) val astroTrain: DataSet[LabeledVector] = astroTrainLibSVM.map(svmNormaliser) val astroTest: DataSet[(Vector, Double)] = astroTestLibSVM.map(svmNormaliser).map(x => (x.vector, x.label)) ``` ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
