Java Deep Learning Cookbook

How to do it...

1. Leave out all the noise features before training the neural network. Remove noise features at the schema transformation stage:

TransformProcess transformProcess = new TransformProcess.Builder(schema) .removeColumns("RowNumber","CustomerId","Surname") .build();    

2. Identify the missing values using the DataVec analysis API:

DataQualityAnalysis analysis = AnalyzeLocal.analyzeQuality(schema,recordReader); System.out.println(analysis); 

3. Remove null values using a schema transformation:

Condition condition = new NullWritableColumnCondition("columnName"); TransformProcess transformProcess = new TransformProcess.Builder(schema)   .conditionalReplaceValueTransform("columnName",new IntWritable(0),condition) .build();

4. Remove NaN ...