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Fix typo (#5399)

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Bart Broere 2020-03-09 12:41:39 +01:00 committed by GitHub
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demo/binary_classification/README.md
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@ -156,7 +156,7 @@ If you want to continue boosting from existing model, say 0002.model, use
```
xgboost will load from 0002.model continue boosting for 2 rounds, and save output to continue.model. However, beware that the training and evaluation data specified in mushroom.conf should not change when you use this function.
#### Use Multi-Threading
When you are working with a large dataset, you may want to take advantage of parallelism. If your compiler supports OpenMP, xgboost is naturally multi-threaded, to set number of parallel running add ```nthread``` parameter to you configuration.
When you are working with a large dataset, you may want to take advantage of parallelism. If your compiler supports OpenMP, xgboost is naturally multi-threaded, to set number of parallel running add ```nthread``` parameter to your configuration.
Eg. ```nthread=10```
Set nthread to be the number of your real cpu (On Unix, this can be found using ```lscpu```)