water.bindings.pojos.ModelMetricsHGLMV3 Maven / Gradle / Ivy
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ModelMetricsHGLMV3 extends ModelMetricsBaseV3 {
/**
* standard error of fixed predictors/effects
*/
public double[] sefe;
/**
* standard error of random effects
*/
public double[] sere;
/**
* dispersion parameter of the mean model (residual variance for LMM)
*/
public double varfix;
/**
* dispersion parameter of the random effects (variance of random effects for GLMM
*/
public double[] varranef;
/**
* fixed coefficient)
*/
public double[] fixef;
/**
* random coefficients
*/
public double[] ranef;
/**
* true if model has converged
*/
public boolean converge;
/**
* number of random columns
*/
public int[] randc;
/**
* deviance degrees of freedom for mean part of the model
*/
public double dfrefe;
/**
* estimates, standard errors of the linear predictor in the dispersion model
*/
public double[] summvc1;
/**
* estimates, standard errors of the linear predictor for dispersion parameter of random effects
*/
public double[][] summvc2;
/**
* log h-likelihood
*/
public double hlik;
/**
* adjusted profile log-likelihood profiled over random effects
*/
public double pvh;
/**
* adjusted profile log-likelihood profiled over fixed and random effects
*/
public double pbvh;
/**
* conditional AIC
*/
public double caic;
/**
* index of the most influential observation
*/
public long bad;
/**
* sum(etai-eta0)^2 where etai is current eta and eta0 is the previous one
*/
public double sumetadiffsquare;
/**
* sum(etai-eta0)^2/sum(etai)^2
*/
public double convergence;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// The model used for this scoring run.
public ModelKeyV3 model;
// The checksum for the model used for this scoring run.
public long modelChecksum;
// The frame used for this scoring run.
public FrameKeyV3 frame;
// The checksum for the frame used for this scoring run.
public long frameChecksum;
// Optional description for this scoring run (to note out-of-bag, sampled data, etc.)
public String description;
// The category (e.g., Clustering) for the model used for this scoring run.
public ModelCategory modelCategory;
// The time in mS since the epoch for the start of this scoring run.
public long scoringTime;
// Predictions Frame.
public FrameV3 predictions;
// The Mean Squared Error of the prediction for this scoring run.
public double mse;
// The Root Mean Squared Error of the prediction for this scoring run.
public double rmse;
// Number of observations.
public long nobs;
// Name of custom metric
public String customMetricName;
// Value of custom metric
public double customMetricValue;
*/
/**
* Public constructor
*/
public ModelMetricsHGLMV3() {
varfix = 0.0;
converge = false;
dfrefe = 0.0;
hlik = 0.0;
pvh = 0.0;
pbvh = 0.0;
caic = 0.0;
bad = 0L;
sumetadiffsquare = 0.0;
convergence = 0.0;
modelChecksum = 0L;
frameChecksum = 0L;
description = "";
scoringTime = 0L;
mse = 0.0;
rmse = 0.0;
nobs = 0L;
customMetricName = "";
customMetricValue = 0.0;
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}