K
- Type of a key in upstream
data.V
- Type of a value in upstream
data.public final class MinMaxScalerPreprocessor<K,V> extends Object implements Preprocessor<K,V>, DeployableObject
a_i = (a_i - min_i) / (max_i - min_i) for all i
,
where i
is a number of column, max_i
is the value of the maximum element in this columns,
min_i
is the value of the minimal element in this column.Constructor and Description |
---|
MinMaxScalerPreprocessor(double[] min,
double[] max,
Preprocessor<K,V> basePreprocessor)
Constructs a new instance of minmaxscaling preprocessor.
|
Modifier and Type | Method and Description |
---|---|
LabeledVector |
apply(K k,
V v)
Applies this preprocessor.
|
List<Object> |
getDependencies()
Returns dependencies of this object that can be object with class defined by client side and unknown for server.
|
double[] |
getMax() |
double[] |
getMin() |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
map
andThen
andThen
public MinMaxScalerPreprocessor(double[] min, double[] max, Preprocessor<K,V> basePreprocessor)
min
- Minimal values.max
- Maximum values.basePreprocessor
- Base preprocessor.public LabeledVector apply(K k, V v)
apply
in interface BiFunction<K,V,LabeledVector>
k
- Key.v
- Value.public double[] getMin()
public double[] getMax()
public List<Object> getDependencies()
getDependencies
in interface DeployableObject
GridGain In-Memory Computing Platform : ver. 8.9.14 Release Date : November 5 2024