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@ -80,12 +80,6 @@ booster = gblinear
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# L2 regularization term on weights, default 0
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# L2 regularization term on weights, default 0
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lambda = 0.01
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lambda = 0.01
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# L1 regularization term on weights, default 0
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# L1 regularization term on weights, default 0
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If ```agaricus.txt.test.buffer``` exists, and automatically loads from binary buffer if possible, this can speedup training process when you do training many times. You can disable it by setting ```use_buffer=0```.
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- Buffer file can also be used as standalone input, i.e if buffer file exists, but original agaricus.txt.test was removed, xgboost will still run
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* Deviation from LibSVM input format: xgboost is compatible with LibSVM format, with the following minor differences:
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- xgboost allows feature index starts from 0
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- for binary classification, the label is 1 for positive, 0 for negative, instead of +1,-1
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- the feature indices in each line *do not* need to be sorted
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alpha = 0.01
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alpha = 0.01
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# L2 regularization term on bias, default 0
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# L2 regularization term on bias, default 0
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lambda_bias = 0.01
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lambda_bias = 0.01
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@ -318,10 +318,6 @@ Command Line Parameters
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***********************
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***********************
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The following parameters are only used in the console version of XGBoost
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The following parameters are only used in the console version of XGBoost
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* ``use_buffer`` [default=1]
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- Whether to create a binary buffer from text input. Doing so normally will speed up loading times
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* ``num_round``
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* ``num_round``
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- The number of rounds for boosting
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- The number of rounds for boosting
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