Regressor (Tribuo 4.0.2 API)

java.lang.Object
- org.tribuo.regression.Regressor

All Implemented Interfaces:

Serializable, Iterable<Regressor.DimensionTuple>, Output<Regressor>

Direct Known Subclasses:

Regressor.DimensionTuple
```
public class Regressor
extends Object
implements Output<Regressor>, Iterable<Regressor.DimensionTuple>
```
An Output for n-dimensional real valued regression.
In addition to the regressed values, it may optionally contain variances. Otherwise the variances are set to Double.NaN.

Within a DataSource or Dataset each Regressor must contain the same set of named dimensions. The dimensions stored in a Regressor are sorted by the natural ordering of their names (i.e., using the String comparator). This allows the use of direct indexing into the elements.

Note fullEquals(org.tribuo.regression.Regressor) compares the dimensions, the regressed values and the variances. However unlike Double.equals(java.lang.Object), if the two variances being compared are set to the sentinel value of Double.NaN, then they are considered equal.

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`static class`	`Regressor.DimensionTuple` A `Regressor` which contains a single dimension, used internally when the model implementation doesn't natively support multi-dimensional regression outputs.

Field Summary

Fields
Modifier and Type Field and Description

static String DEFAULT_NAME

static double TOLERANCE

Fields
Modifier and Type	Field and Description
`static String`	`DEFAULT_NAME`
`static double`	`TOLERANCE`

Constructor Summary

Constructors
Constructor and Description
`Regressor(Regressor.DimensionTuple[] dimensions)` Constructs a regressor from the supplied dimension tuples.
`Regressor(String[] names, double[] values)` Constructs a regressor from the supplied named values.
`Regressor(String[] names, double[] values, double[] variances)` Constructs a regressor from the supplied named values.
`Regressor(String name, double value)` Constructs a regressor containing a single dimension, using `Double.NaN` as the variance.
`Regressor(String name, double value, double variance)` Constructs a regressor containing a single dimension.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`Regressor`	`copy()` Deep copy of the output up to it's immutable state.
`static Regressor`	`createFromPairList(List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>> dimensions)` Creates a Regressor from a list of dimension tuples.
`boolean`	`equals(Object o)` Regressors are equal if they have the same number of dimensions and equal dimension names.
`static String[]`	`extractNames(OutputInfo<Regressor> info)` Extracts the names from the supplied Regressor domain in their canonical order.
`boolean`	`fullEquals(Regressor other)` Compares other to this output.
`Optional<Regressor.DimensionTuple>`	`getDimension(String name)` Returns a dimension tuple for the requested dimension, or optional empty if it's not valid.
`String`	`getDimensionNamesString()` Returns a comma separated list of the dimension names.
`String`	`getDimensionNamesString(char separator)` Returns a delimiter separated list of the dimension names.
`String[]`	`getNames()` The names of the dimensions.
`String`	`getSerializableForm(boolean includeConfidence)` Generates a String suitable for writing to a csv or json file.
`double[]`	`getValues()` Returns the regression values.
`double[]`	`getVariances()` The variances of the regressed values, if known.
`int`	`hashCode()` Regressor's hashcode is based on the hash of the dimension names.
`Iterator<Regressor.DimensionTuple>`	`iterator()`
`static com.oracle.labs.mlrg.olcut.util.Pair<String,Double>`	`parseElement(int idx, String s)` Parses a string of the form:
`static Regressor`	`parseString(String s)` Parses a string of the form:
`static Regressor`	`parseString(String s, char splitChar)` Parses a string of the form:
`int`	`size()` Returns the number of dimensions in this regressor.
`String`	`toString()`

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

Methods inherited from interface java.lang.Iterable
forEach, spliterator

- Field Detail
  - TOLERANCE
```
public static final double TOLERANCE
```
    See Also:
    
    Constant Field Values
  - DEFAULT_NAME
```
public static final String DEFAULT_NAME
```
    See Also:
    
    Constant Field Values
- Constructor Detail
  - Regressor
```
public Regressor(String[] names,
                 double[] values,
                 double[] variances)
```
    Constructs a regressor from the supplied named values. Throws IllegalArgumentException if the arrays are not all the same size.
    
    Parameters:
    
    names - The names of the dimensions.
    
    values - The values of the dimensions.
    
    variances - The variances of the specified values.
  - Regressor
```
public Regressor(String[] names,
                 double[] values)
```
    Constructs a regressor from the supplied named values. Uses Double.NaN as the variances.
    
    Parameters:
    
    names - The names of the dimensions.
    
    values - The values of the dimensions.
  - Regressor
```
public Regressor(Regressor.DimensionTuple[] dimensions)
```
    Constructs a regressor from the supplied dimension tuples.
    
    Parameters:
    
    dimensions - The named values to use.
  - Regressor
```
public Regressor(String name,
                 double value)
```
    Constructs a regressor containing a single dimension, using Double.NaN as the variance.
    
    Parameters:
    
    name - The name of the dimension.
    
    value - The value of the dimension.
  - Regressor
```
public Regressor(String name,
                 double value,
                 double variance)
```
    Constructs a regressor containing a single dimension.
    
    Parameters:
    
    name - The name of the dimension.
    
    value - The value of the dimension.
    
    variance - The variance of this value.
- Method Detail
  - size
```
public int size()
```
    Returns the number of dimensions in this regressor.
    
    Returns:
    
    The number of dimensions.
  - getNames
```
public String[] getNames()
```
    The names of the dimensions. Always sorted by their natural ordering.
    
    Returns:
    
    The names of the dimensions.
  - getValues
```
public double[] getValues()
```
    Returns the regression values.
    
    Returns:
    
    The regression values.
  - getVariances
```
public double[] getVariances()
```
    The variances of the regressed values, if known. Returns Double.NaN otherwise.
    
    Returns:
    
    The variance of the regressed values.
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - getDimension
```
public Optional<Regressor.DimensionTuple> getDimension(String name)
```
    Returns a dimension tuple for the requested dimension, or optional empty if it's not valid.
    
    Parameters:
    
    name - The dimension name.
    
    Returns:
    
    A tuple representing that dimension.
  - iterator
```
public Iterator<Regressor.DimensionTuple> iterator()
```
    Specified by:
    
    iterator in interface Iterable<Regressor.DimensionTuple>
  - copy
```
public Regressor copy()
```
    Description copied from interface: Output
    
    Deep copy of the output up to it's immutable state.
    
    Specified by:
    
    copy in interface Output<Regressor>
    
    Returns:
    
    A copy of the output.
  - getSerializableForm
```
public String getSerializableForm(boolean includeConfidence)
```
    Description copied from interface: Output
    
    Generates a String suitable for writing to a csv or json file.
    
    Specified by:
    
    getSerializableForm in interface Output<Regressor>
    
    Parameters:
    
    includeConfidence - Include whatever confidence score the label contains, if known.
    
    Returns:
    
    A String representation of this Output.
  - fullEquals
```
public boolean fullEquals(Regressor other)
```
    Description copied from interface: Output
    
    Compares other to this output. Uses all score values and the strings.
    
    Specified by:
    
    fullEquals in interface Output<Regressor>
    
    Parameters:
    
    other - Another output instance.
    
    Returns:
    
    True if the other instance has value equality to this instance. False otherwise.
  - equals
```
public boolean equals(Object o)
```
    Regressors are equal if they have the same number of dimensions and equal dimension names.
    
    Overrides:
    
    equals in class Object
    
    Parameters:
    
    o - An object.
    
    Returns:
    
    True if Object is a Regressor with the same dimension names, false otherwise.
  - hashCode
```
public int hashCode()
```
    Regressor's hashcode is based on the hash of the dimension names.
    It's cached on first access.
    
    Overrides:
    
    hashCode in class Object
    
    Returns:
    
    A hashcode.
  - getDimensionNamesString
```
public String getDimensionNamesString()
```
    Returns a comma separated list of the dimension names.
    
    Returns:
    
    The dimension names comma separated.
  - getDimensionNamesString
```
public String getDimensionNamesString(char separator)
```
    Returns a delimiter separated list of the dimension names.
    
    Parameters:
    
    separator - The separator to use.
    
    Returns:
    
    The dimension names.
  - extractNames
```
public static String[] extractNames(OutputInfo<Regressor> info)
```
    Extracts the names from the supplied Regressor domain in their canonical order.
    
    Parameters:
    
    info - The OutputInfo to use.
    
    Returns:
    
    The dimension names from this domain.
  - parseString
```
public static Regressor parseString(String s)
```
    Parses a string of the form:
```
 dimension-name=output,...,dimension-name=output
 
```
    where output must be readable by Double.parseDouble(java.lang.String).
    Parameters:
    
    s - The string form of a multiple regressor.
    
    Returns:
    
    A regressor parsed from the input string.
  - parseString
```
public static Regressor parseString(String s,
                                    char splitChar)
```
    Parses a string of the form:
```
 dimension-name=output<splitChar>...<splitChar>dimension-name=output
 
```
    where output must be readable by Double.parseDouble(java.lang.String).
    Parameters:
    
    s - The string form of a regressor.
    
    splitChar - The char to split on.
    
    Returns:
    
    A regressor parsed from the input string.
  - parseElement
```
public static com.oracle.labs.mlrg.olcut.util.Pair<String,Double> parseElement(int idx,
                                                                               String s)
```
    Parses a string of the form:
```
 dimension-name=output-double
 
```
    where the output must be readable by Double.parseDouble(java.lang.String).
    Parameters:
    
    idx - The index of this string in a list.
    
    s - The string form of a single dimension from a regressor.
    
    Returns:
    
    A tuple representing the dimension name and the value.
  - createFromPairList
```
public static Regressor createFromPairList(List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>> dimensions)
```
    Creates a Regressor from a list of dimension tuples.
    
    Parameters:
    
    dimensions - The dimensions to use.
    
    Returns:
    
    A Regressor representing these dimensions.

Class Regressor

Nested Class Summary

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface java.lang.Iterable

Field Detail

TOLERANCE

DEFAULT_NAME

Constructor Detail

Regressor

Regressor

Regressor

Regressor

Regressor

Method Detail

size

getNames

getValues

getVariances

toString

getDimension

iterator

copy

getSerializableForm

fullEquals

equals

hashCode

getDimensionNamesString

getDimensionNamesString

extractNames

parseString

parseString

parseElement

createFromPairList