HGLMParametersV3 (h2o-bindings 3.46.0 API)

java.lang.Object
- water.bindings.pojos.SchemaV3
- - water.bindings.pojos.ModelParametersSchemaV3
  - - water.bindings.pojos.HGLMParametersV3

public class HGLMParametersV3
extends ModelParametersSchemaV3

Field Summary

Fields
Modifier and Type	Field and Description
`double`	`emEpsilon` Converge if beta/ubeta/tmat/tauEVar changes less (using L-infinity norm) than em esilon.
`GLMFamily`	`family` Family.
`boolean`	`genSynData` If true, add gaussian noise with variance specified in parms._tau_e_var_init.
`java.lang.String`	`groupColumn` Group column is the column that is categorical and used to generate the groups in HGLM
`double[]`	`initialFixedEffects` An array that contains initial values of the fixed effects coefficient.
`FrameKeyV3`	`initialRandomEffects` A H2OFrame id that contains initial values of the random effects coefficient.
`FrameKeyV3`	`initialTMatrix` A H2OFrame id that contains initial values of the T matrix.
`int`	`maxIterations` Maximum number of iterations.
`HGLMMethod`	`method` We only implemented EM as a method to obtain the fixed, random coefficients and the various variances.
`GLMMissingValuesHandling`	`missingValuesHandling` Handling of missing values.
`FrameKeyV3`	`plugValues` Plug Values (a single row frame containing values that will be used to impute missing values of the training/validation frame, use with conjunction missing_values_handling = PlugValues).
`GLMFamily`	`randFamily` Set distribution of random effects.
`java.lang.String[]`	`randomColumns` Random columns indices for HGLM.
`boolean`	`randomIntercept` If true, will allow random component to the GLM coefficients.
`int`	`scoreIterationInterval` Perform scoring for every score_iteration_interval iterations.
`long`	`seed` Seed for pseudo random number generator (if applicable).
`double`	`tauEVarInit` Initial variance of random noise.
`double`	`tauUVarInit` Initial variance of random coefficient effects.

Constructor Summary

Constructors
Constructor and Description

HGLMParametersV3()
Public constructor

Constructors
Constructor and Description
`HGLMParametersV3()` Public constructor

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type Method and Description

java.lang.String toString()
Return the contents of this object as a JSON String.
- Methods inherited from class java.lang.Object
  clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`toString()` Return the contents of this object as a JSON String.

- Field Detail
  - scoreIterationInterval
```
@SerializedName(value="score_iteration_interval")
public int scoreIterationInterval
```
    Perform scoring for every score_iteration_interval iterations.
  - seed
```
public long seed
```
    Seed for pseudo random number generator (if applicable).
  - missingValuesHandling
```
@SerializedName(value="missing_values_handling")
public GLMMissingValuesHandling missingValuesHandling
```
    Handling of missing values. Either MeanImputation, Skip or PlugValues.
  - plugValues
```
@SerializedName(value="plug_values")
public FrameKeyV3 plugValues
```
    Plug Values (a single row frame containing values that will be used to impute missing values of the training/validation frame, use with conjunction missing_values_handling = PlugValues).
  - family
```
public GLMFamily family
```
    Family. Only gaussian is supported now.
  - randFamily
```
@SerializedName(value="rand_family")
public GLMFamily randFamily
```
    Set distribution of random effects. Only Gaussian is implemented now.
  - maxIterations
```
@SerializedName(value="max_iterations")
public int maxIterations
```
    Maximum number of iterations. Value should >=1. A value of 0 is only set when only the model coefficient names and model coefficient dimensions are needed.
  - initialFixedEffects
```
@SerializedName(value="initial_fixed_effects")
public double[] initialFixedEffects
```
    An array that contains initial values of the fixed effects coefficient.
  - initialRandomEffects
```
@SerializedName(value="initial_random_effects")
public FrameKeyV3 initialRandomEffects
```
    A H2OFrame id that contains initial values of the random effects coefficient. The row names shouldbe the random coefficient names. If you are not sure what the random coefficient names are, build HGLM model with max_iterations = 0 and checkout the model output field random_coefficient_names. The number of rows of this frame should be the number of level 2 units. Again, to figure this out, build HGLM model with max_iterations=0 and check out the model output field group_column_names. The number of rows should equal the length of thegroup_column_names.
  - initialTMatrix
```
@SerializedName(value="initial_t_matrix")
public FrameKeyV3 initialTMatrix
```
    A H2OFrame id that contains initial values of the T matrix. It should be a positive symmetric matrix.
  - tauUVarInit
```
@SerializedName(value="tau_u_var_init")
public double tauUVarInit
```
    Initial variance of random coefficient effects. If set, should provide a value > 0.0. If not set, will be randomly set in the model building process.
  - tauEVarInit
```
@SerializedName(value="tau_e_var_init")
public double tauEVarInit
```
    Initial variance of random noise. If set, should provide a value > 0.0. If not set, will be randomly set in the model building process.
  - randomColumns
```
@SerializedName(value="random_columns")
public java.lang.String[] randomColumns
```
    Random columns indices for HGLM.
  - method
```
public HGLMMethod method
```
    We only implemented EM as a method to obtain the fixed, random coefficients and the various variances.
  - emEpsilon
```
@SerializedName(value="em_epsilon")
public double emEpsilon
```
    Converge if beta/ubeta/tmat/tauEVar changes less (using L-infinity norm) than em esilon. ONLY applies to EM method.
  - randomIntercept
```
@SerializedName(value="random_intercept")
public boolean randomIntercept
```
    If true, will allow random component to the GLM coefficients.
  - groupColumn
```
@SerializedName(value="group_column")
public java.lang.String groupColumn
```
    Group column is the column that is categorical and used to generate the groups in HGLM
  - genSynData
```
@SerializedName(value="gen_syn_data")
public boolean genSynData
```
    If true, add gaussian noise with variance specified in parms._tau_e_var_init.
- Constructor Detail
  - HGLMParametersV3
```
public HGLMParametersV3()
```
    Public constructor
- Method Detail
  - toString
```
public java.lang.String toString()
```
    Return the contents of this object as a JSON String.
    
    Overrides:
    
    toString in class ModelParametersSchemaV3

Class HGLMParametersV3

Field Summary

Fields inherited from class water.bindings.pojos.ModelParametersSchemaV3

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

scoreIterationInterval

seed

missingValuesHandling

plugValues

family

randFamily

maxIterations

initialFixedEffects

initialRandomEffects

initialTMatrix

tauUVarInit

tauEVarInit

randomColumns

method

emEpsilon

randomIntercept

groupColumn

genSynData

Constructor Detail

HGLMParametersV3

Method Detail

toString