29a1356669
* Deprecate `reg:linear' in favor of `reg:squarederror'. * Replace the use of `reg:linear'. * Replace the use of `silent`.
30 lines
1005 B
Plaintext
30 lines
1005 B
Plaintext
# General Parameters, see comment for each definition
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# choose the tree booster, can also change to gblinear
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booster = gbtree
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# this is the only difference with classification, use reg:squarederror to do linear classification
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# when labels are in [0,1] we can also use reg:logistic
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objective = reg:squarederror
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# Tree Booster Parameters
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# step size shrinkage
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eta = 1.0
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# minimum loss reduction required to make a further partition
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gamma = 1.0
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# minimum sum of instance weight(hessian) needed in a child
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min_child_weight = 1
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# maximum depth of a tree
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max_depth = 5
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base_score = 2001
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# Task parameters
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# the number of round to do boosting
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num_round = 100
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# 0 means do not save any model except the final round model
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save_period = 0
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# The path of training data
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data = "yearpredMSD.libsvm.train"
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# The path of validation data, used to monitor training process, here [test] sets name of the validation set
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eval[test] = "yearpredMSD.libsvm.test"
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# The path of test data
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#test:data = "yearpredMSD.libsvm.test"
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