Comments (2)
vlevel is used to control how to output result's probabilities. If probabilities are not required in your scenarios, you could set vlevel to 0, and then you will get performance gains. If you want to have probabilities, you may need to optimize existing code, such as converting features weights from double type to integer type, and calculating them by integer type.
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Another way is to optimize "log" and "exp" function. Here are some articles maybe helpful for you:
http://www.machinedlearnings.com/2011/06/fast-approximate-logarithm-exponential.html
http://www.quinapalus.com/efunc.html
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Related Issues (15)
- System.ArgumentOutOfRangeException in buidFeatures method from DecoderTagger class. HOT 4
- Limiting predicted tags using a dictionary HOT 3
- AdvUtils.DoubleArrayTrieSearch does not have Load Method HOT 2
- Question in decoding performance.
- Retrain with new tags?
- Error in decoding HOT 1
- format Errors HOT 1
- problem with template file HOT 1
- feature_cache_size HOT 2
- Format errors with any training data
- how to compile this project with mono in ubuntu?
- Some feedback about trainfile size and decode inputfile form
- An unhandled exception of type 'System.OutOfMemoryException' occurred in AdvUtils.dll HOT 7
- Build lexical dictionary failed HOT 8
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