AbstractDyadScaler (jaicore-ml 0.1.3 API)

java.lang.Object
- ai.libs.jaicore.ml.dyadranking.util.AbstractDyadScaler

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

DyadMinMaxScaler, DyadStandardScaler, DyadUnitIntervalScaler
```
public abstract class AbstractDyadScaler
extends java.lang.Object
implements java.io.Serializable
```
A scaler that can be fit to a certain dataset and then be used to standardize datasets, i.e. transform the data to have a mean of 0 and a standard deviation of 1 according to the data it was fit to.

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`protected org.apache.commons.math3.stat.descriptive.SummaryStatistics[]`	`statsX`
`protected org.apache.commons.math3.stat.descriptive.SummaryStatistics[]`	`statsY`

Constructor Summary

Constructors
Constructor and Description

AbstractDyadScaler()

Constructors
Constructor and Description
`AbstractDyadScaler()`

Method Summary

All Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`fit(DyadRankingDataset dataset)` Fits the standard scaler to the dataset.
`void`	`fitTransform(DyadRankingDataset dataset)` Fits the standard scaler to the dataset and transforms the entire dataset according to the mean and standard deviation of the dataset.
`java.lang.String`	`getPrettyMeansString()` Returns a String for the means of all features this scaler has been fit to.
`java.lang.String`	`getPrettySTDString()` Prints the standard devations of all features this scaler has been fit to.
`org.apache.commons.math3.stat.descriptive.SummaryStatistics[]`	`getStatsX()`
`org.apache.commons.math3.stat.descriptive.SummaryStatistics[]`	`getStatsY()`
`void`	`transform(DyadRankingDataset dataset)` Transforms the entire dataset according to the mean and standard deviation of the data the scaler has been fit to.
`abstract void`	`transformAlternatives(Dyad dyad, java.util.List<java.lang.Integer> ignoredIndices)` Transforms only the alternatives of each dyad according to the mean and standard deviation of the data the scaler has been fit to.
`void`	`transformAlternatives(DyadRankingDataset dataset)` Transforms only the alternatives of each dyad according to the mean and standard deviation of the data the scaler has been fit to.
`void`	`transformAlternatives(DyadRankingDataset dataset, java.util.List<java.lang.Integer> ignoredIndices)` Transforms only the alternatives of each dyad in a `DyadRankingDataset` according to the mean and standard deviation of the data the scaler has been fit to.
`void`	`transformAlternatives(IDyadRankingInstance drInstance, java.util.List<java.lang.Integer> ignoredIndices)` Transforms only the alternatives of each dyad in an `IDyadRankingInstance` according to the mean and standard deviation of the data the scaler has been fit to.
`abstract void`	`transformInstaceVector(ai.libs.jaicore.math.linearalgebra.Vector vector, java.util.List<java.lang.Integer> ignoredIndices)` Transforms an instance feature vector.
`abstract void`	`transformInstances(Dyad dyad, java.util.List<java.lang.Integer> ignoredIndices)` Transforms only the instances of each dyad according to the mean and standard deviation of the data the scaler has been fit to.
`void`	`transformInstances(DyadRankingDataset dataset)` Transforms only the instances of each dyad according to the mean and standard of the data the scaler has been fit to.
`void`	`transformInstances(DyadRankingDataset dataset, java.util.List<java.lang.Integer> ignoredIndices)` Transforms only the instances of each dyad in a `DyadRankingDataset` according to the mean and standard deviation of the data the scaler has been fit to.
`void`	`transformInstances(DyadRankingInstance drInstance, java.util.List<java.lang.Integer> ignoredIndices)` Transforms only the instances of each dyad in a `DyadRankingInstance` according to the mean and standard deviation of the data the scaler has been fit to.
`void`	`transformInstances(SparseDyadRankingInstance drInstance, java.util.List<java.lang.Integer> ignoredIndices)` Transforms only the instances of each dyad in a `SparseDyadRankingInstance` according to the mean and standard deviation of the data the scaler has been fit to.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - statsX
```
protected org.apache.commons.math3.stat.descriptive.SummaryStatistics[] statsX
```
  - statsY
```
protected org.apache.commons.math3.stat.descriptive.SummaryStatistics[] statsY
```
- Constructor Detail
  - AbstractDyadScaler
```
public AbstractDyadScaler()
```
- Method Detail
  - getStatsX
```
public org.apache.commons.math3.stat.descriptive.SummaryStatistics[] getStatsX()
```
  - getStatsY
```
public org.apache.commons.math3.stat.descriptive.SummaryStatistics[] getStatsY()
```
  - fit
```
public void fit(DyadRankingDataset dataset)
```
    Fits the standard scaler to the dataset.
    
    Parameters:
    
    dataset - The dataset the scaler should be fit to.
  - transform
```
public void transform(DyadRankingDataset dataset)
```
    Transforms the entire dataset according to the mean and standard deviation of the data the scaler has been fit to.
    
    Parameters:
    
    dataset - The dataset to be standardized.
  - transformInstances
```
public void transformInstances(DyadRankingDataset dataset)
```
    Transforms only the instances of each dyad according to the mean and standard of the data the scaler has been fit to.
    
    Parameters:
    
    dataset - The dataset of which the instances are to be standardized.
  - transformAlternatives
```
public void transformAlternatives(DyadRankingDataset dataset)
```
    Transforms only the alternatives of each dyad according to the mean and standard deviation of the data the scaler has been fit to.
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
  - transformInstances
```
public abstract void transformInstances(Dyad dyad,
                                        java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms only the instances of each dyad according to the mean and standard deviation of the data the scaler has been fit to. The attributes with indices contained in ignoredIndices are not transformed. {
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
    
    ignoredIndices - The List of indices that are been ignored by the scaler.
  - transformAlternatives
```
public abstract void transformAlternatives(Dyad dyad,
                                           java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms only the alternatives of each dyad according to the mean and standard deviation of the data the scaler has been fit to.
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
    
    ignoredIndices - The List of indices that are been ignored by the scaler.
  - transformInstaceVector
```
public abstract void transformInstaceVector(ai.libs.jaicore.math.linearalgebra.Vector vector,
                                            java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms an instance feature vector.
    
    Parameters:
    
    Instance - vector to be transformed
    
    ignoredIndices -
  - transformInstances
```
public void transformInstances(SparseDyadRankingInstance drInstance,
                               java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms only the instances of each dyad in a SparseDyadRankingInstance according to the mean and standard deviation of the data the scaler has been fit to. The attributes with indices contained in ignoredIndices are not transformed. {
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
    
    ignoredIndices - The List of indices that are been ignored by the scaler.
  - transformInstances
```
public void transformInstances(DyadRankingInstance drInstance,
                               java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms only the instances of each dyad in a DyadRankingInstance according to the mean and standard deviation of the data the scaler has been fit to. The attributes with indices contained in ignoredIndices are not transformed. {
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
    
    ignoredIndices - The List of indices that are been ignored by the scaler.
  - transformAlternatives
```
public void transformAlternatives(IDyadRankingInstance drInstance,
                                  java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms only the alternatives of each dyad in an IDyadRankingInstance according to the mean and standard deviation of the data the scaler has been fit to. The attributes with indices contained in ignoredIndices are not transformed. {
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
    
    ignoredIndices - The List of indices that are been ignored by the scaler.
  - transformInstances
```
public void transformInstances(DyadRankingDataset dataset,
                               java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms only the instances of each dyad in a DyadRankingDataset according to the mean and standard deviation of the data the scaler has been fit to. The attributes with indices contained in ignoredIndices are not transformed. {
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
    
    ignoredIndices - The List of indices that are been ignored by the scaler.
  - transformAlternatives
```
public void transformAlternatives(DyadRankingDataset dataset,
                                  java.util.List<java.lang.Integer> ignoredIndices)
```
    Transforms only the alternatives of each dyad in a DyadRankingDataset according to the mean and standard deviation of the data the scaler has been fit to. The attributes with indices contained in ignoredIndices are not transformed. {
    
    Parameters:
    
    dataset - The dataset of which the alternatives are to be standardized.
    
    ignoredIndices - The List of indices that are been ignored by the scaler.
  - fitTransform
```
public void fitTransform(DyadRankingDataset dataset)
```
    Fits the standard scaler to the dataset and transforms the entire dataset according to the mean and standard deviation of the dataset.
    
    Parameters:
    
    dataset - The dataset to be standardized.
  - getPrettySTDString
```
public java.lang.String getPrettySTDString()
```
    Prints the standard devations of all features this scaler has been fit to.
  - getPrettyMeansString
```
public java.lang.String getPrettyMeansString()
```
    Returns a String for the means of all features this scaler has been fit to.

Class AbstractDyadScaler

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

statsX

statsY

Constructor Detail

AbstractDyadScaler

Method Detail

getStatsX

getStatsY

fit

transform

transformInstances

transformAlternatives

transformInstances

transformAlternatives

transformInstaceVector

transformInstances

transformInstances

transformAlternatives

transformInstances

transformAlternatives

fitTransform

getPrettySTDString

getPrettyMeansString