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auditor (version 1.3.5)

Model Audit - Verification, Validation, and Error Analysis

Description

Provides an easy to use unified interface for creating validation plots for any model. The 'auditor' helps to avoid repetitive work consisting of writing code needed to create residual plots. This visualizations allow to asses and compare the goodness of fit, performance, and similarity of models.

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Version

Install

install.packages('auditor')

Monthly Downloads

1,184

Version

1.3.5

License

GPL

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/ModelOriented/auditor

Maintainer

Alicja Gosiewska

Last Published

October 30th, 2023

Functions in auditor (1.3.5)

Plot Autocorrelation Function in D3 with r2d3 package.

Regression Receiver Operating Characteristic (RROC) in D3 with r2d3 package.

plot_halfnormal

Half-Normal plot

plot_correlation

Correlation of Model's Residuals Plot

plot_cooksdistance

Influence of Observations Plot

Autocorrelation Function Plot

Regression Receiver Operating Characteristic (RROC)

plot_residual_boxplot

Plot Boxplots of Residuals

Plot Residuals vs Observed, Fitted or Variable Values

plot_autocorrelation

Autocorrelation of Residuals Plot

plot_scalelocation

Scale location plot

plot_prediction

Predicted response vs Observed or Variable Values

Receiver Operating Characteristic (ROC) in D3 with r2d3 package.

plotD3_residual

Plot Residuals vs Observed, Fitted or Variable Values in D3 with r2d3 package.

print.auditor_model_evaluation

Prints Model Evaluation Summary

print.auditor_model_halfnormal

Prints Model Halfnormal Summary

Principal Component Analysis of models

plotD3_scalelocation

Scale Location Plot in D3 with r2d3 package.

Model Ranking Plot

Model Scores computations

Durbin-Watson Score

print.auditor_score

Prints of Models Scores

Area under precision-recall curve

Gini Coefficient

score_halfnormal

Half-Normal Score

plot_residual_density

Residual Density Plot

score_one_minus_gini

One minus Gini Coefficient

Regression Error Characteristic Curves (REC)

score_one_minus_precision

One Minus Precision

print.auditor_model_performance

Prints Model Performance Summary

score_specificity

print.auditor_model_residual

Prints Model Residual Summary

Mean Square Error

Area Under ROC Curve (AUC)

Mean Absolute Error

score_cooksdistance

Score based on Cooks Distance

Area Over the Curve for REC Curves

Area Over the Curve for RROC Curves

score_precision

Precision-Recall Curve (PRC)

print.auditor_model_cooksdistance

Prints Model Cook's Distances Summary

Two-sided Cumulative Distribution Function

score_one_minus_acc

One minus accuracy

score_one_minus_auprc

One Minus area under precision-recall curve

score_one_minus_auc

One minus Area Under ROC Curve (AUC)

Root Mean Square Error

score_one_minus_recall

One minus recall

score_one_minus_specificity

One minus specificity

score_one_minus_f1

One Minus F1 Score

check_residuals_autocorrelation

Checks for autocorrelation in target variable or in residuals

model_evaluation

Create model evaluation explanation

check_residuals

Automated tests for model residuals

Artificial auditorData

model_halfnormal

Create Halfnormal Explanation

check_residuals_outliers

Checks for outliers

plotD3_prediction

Plot Prediction vs Target, Observed or Variable Values in D3 with r2d3 package.

Model Diagnostic Plots

Plot LIFT in D3 with r2d3 package.

plotD3_autocorrelation

Autocorrelation Plot in D3 with r2d3 package.

check_residuals_trend

Checks for trend in residuals

model_cooksdistance

Cook's distances

model_performance

Create Model Performance Explanation

Create Model Residuals Explanation

plotD3_halfnormal

Plot Half-Normal in D3 with r2d3 package.

plotD3_cooksdistance

Influence of observations Plot in D3 with r2d3 package.

Regression Error Characteristic Curves (REC) in D3 with r2d3 package.

Model Diagnostic Plots in D3 with r2d3 package.