WEKA: issue with attribute scales?

According to the Weka Javadocs SMO "normalizes all attributes by default. (Note that the coefficients in the output are based on the normalized/standardized data, not the original data. )" I.e.

, you'll get erroneous normalization if your training set doesn't cover the full range for each attribute. How bad that is depends on your data.

According to the Weka Javadocs, SMO "normalizes all attributes by default. (Note that the coefficients in the output are based on the normalized/standardized data, not the original data. )" I.e.

, you'll get erroneous normalization if your training set doesn't cover the full range for each attribute. How bad that is depends on your data. I suggest you try training both with and without normalization (use setFeatureSpaceNormalization(false) to turn it off) and see what works best.

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