Method setUpVecs

JSAT/src/jsat/classifiers/linear/SMIDAS.java:285–320

(DataSet dataSet)

    }

    private Vec[] setUpVecs(DataSet dataSet)
    {
        obvMin = new double[dataSet.getNumNumericalVars()];
        Arrays.fill(obvMin, Double.POSITIVE_INFINITY);
        obvMax = new double[dataSet.getNumNumericalVars()];
        Arrays.fill(obvMax, Double.NEGATIVE_INFINITY);
        Vec[] x = new Vec[dataSet.getSampleSize()];    
        for(int i = 0; i < dataSet.getSampleSize(); i++)
        {
            x[i] = dataSet.getDataPoint(i).getNumericalValues();

            for(IndexValue iv : x[i])
            {
                int j = iv.getIndex();
                double v = iv.getValue();
                obvMin[j] = Math.min(obvMin[j], v);
                obvMax[j] = Math.max(obvMax[j], v);
            }
        }
        
        if(x[0].isSparse())//Assume implicit min zeros from sparsity
            for(int i = 0; i < obvMin.length; i++)
                obvMin[i] = Math.min(obvMin[i], 0);
        
        if(!reScale)
        {
            for(double min : obvMin)
                if(min < -1)
                    throw new FailedToFitException("Values must be in the range [-1,1], " + min + " violation encountered");
            for(double max : obvMax)
                if(max > 1)
                    throw new FailedToFitException("Values must be in the range [-1,1], " + max + " violation encountered");
            
        }
        return x;
    }
    
}