class QuantileDMatrix extends DMatrix
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new
QuantileDMatrix(iter: Iterator[ColumnBatch], ref: Option[QuantileDMatrix], missing: Float, maxBin: Int, nthread: Int)
Create QuantileDMatrix from iterator based on the array interface
Create QuantileDMatrix from iterator based on the array interface
- iter
the XGBoost ColumnBatch batch to provide the corresponding array interface
- ref
The reference QuantileDMatrix that provides quantile information, needed when creating validation/test dataset with QuantileDMatrix. Supplying the training DMatrix as a reference means that the same quantisation applied to the training data is applied to the validation/test data
- missing
the missing value
- maxBin
the max bin
- nthread
the parallelism
- Exceptions thrown
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new
QuantileDMatrix(iter: Iterator[ColumnBatch], missing: Float, maxBin: Int, nthread: Int)
Create QuantileDMatrix from iterator based on the array interface
Create QuantileDMatrix from iterator based on the array interface
- iter
the XGBoost ColumnBatch batch to provide the corresponding array interface
- missing
the missing value
- maxBin
the max bin
- nthread
the parallelism
- Exceptions thrown
Value Members
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!=(arg0: Any): Boolean
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def
delete(): Unit
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eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
getBaseMargin: Array[Float]
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final
def
getClass(): Class[_]
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def
getFeatureNames: Array[String]
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def
getFeatureTypes: Array[String]
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def
getGroup(): Array[Int]
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def
getHandle: Long
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def
getLabel: Array[Float]
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def
getWeight: Array[Float]
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def
hashCode(): Int
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ne(arg0: AnyRef): Boolean
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def
nonMissingNum: Long
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def
notify(): Unit
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def
notifyAll(): Unit
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def
rowNum: Long
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def
saveBinary(filePath: String): Unit
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- DMatrix
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def
setBaseMargin(column: Column): Unit
set base margin of dmatrix from column array interface
set base margin of dmatrix from column array interface
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- QuantileDMatrix → DMatrix
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- @throws( classOf[XGBoostError] )
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def
setBaseMargin(baseMargin: Array[Array[Float]]): Unit
if specified, xgboost will start from this init margin can be used to specify initial prediction to boost from
if specified, xgboost will start from this init margin can be used to specify initial prediction to boost from
- baseMargin
base margin
- Definition Classes
- QuantileDMatrix → DMatrix
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- @throws( classOf[XGBoostError] )
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def
setBaseMargin(baseMargin: Array[Float]): Unit
if specified, xgboost will start from this init margin can be used to specify initial prediction to boost from
if specified, xgboost will start from this init margin can be used to specify initial prediction to boost from
- baseMargin
base margin
- Definition Classes
- QuantileDMatrix → DMatrix
- Annotations
- @throws( classOf[XGBoostError] )
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def
setFeatureNames(values: Array[String]): Unit
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def
setFeatureTypes(values: Array[String]): Unit
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def
setGroup(group: Array[Int]): Unit
Set group sizes of DMatrix (used for ranking)
Set group sizes of DMatrix (used for ranking)
- group
group size as array
- Definition Classes
- QuantileDMatrix → DMatrix
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- @throws( classOf[XGBoostError] )
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def
setLabel(column: Column): Unit
Set label of DMatrix from array interface
Set label of DMatrix from array interface
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- QuantileDMatrix → DMatrix
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- @throws( classOf[XGBoostError] )
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def
setLabel(labels: Array[Float]): Unit
set label of dmatrix
set label of dmatrix
- labels
labels
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- QuantileDMatrix → DMatrix
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def
setQueryId(column: Column): Unit
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def
setQueryId(qid: Array[Int]): Unit
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def
setWeight(column: Column): Unit
set weight of dmatrix from column array interface
set weight of dmatrix from column array interface
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- QuantileDMatrix → DMatrix
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- @throws( classOf[XGBoostError] )
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def
setWeight(weights: Array[Float]): Unit
set weight of each instance
set weight of each instance
- weights
weights
- Definition Classes
- QuantileDMatrix → DMatrix
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- @throws( classOf[XGBoostError] )
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def
slice(rowIndex: Array[Int]): DMatrix
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