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DALEX (version 2.3.0)

moDel Agnostic Language for Exploration and eXplanation

Description

Unverified black box model is the path to the failure. Opaqueness leads to distrust. Distrust leads to ignoration. Ignoration leads to rejection. DALEX package xrays any model and helps to explore and explain its behaviour. Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance. But such black-box models usually lack of direct interpretability. DALEX package contains various methods that help to understand the link between input variables and model output. Implemented methods help to explore model on the level of a single instance as well as a level of the whole dataset. All model explainers are model agnostic and can be compared across different models. DALEX package is the cornerstone for 'DrWhy.AI' universe of packages for visual model exploration. Find more details in (Biecek 2018) .

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Version

Install

install.packages('DALEX')

Monthly Downloads

5,411

Version

2.3.0

License

GPL

Issues

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Stars

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Last Published

July 28th, 2021

Functions in DALEX (2.3.0)

install_dependencies

Install all dependencies for the DALEX package
fifa

FIFA 20 preprocessed data
plot.model_performance

Plot Dataset Level Model Performance Explanations
apartments

Apartments Data
plot.model_parts

Plot Variable Importance Explanations
print.description

Print Natural Language Descriptions
plot.model_diagnostics

Plot Dataset Level Model Diagnostics
predict_profile

Instance Level Profile as Ceteris Paribus
model_parts

Dataset Level Variable Importance as Change in Loss Function after Variable Permutations
print.model_profile

Print Dataset Level Model Profile
model_performance

Dataset Level Model Performance Measures
variable_effect

Dataset Level Variable Effect as Partial Dependency Profile or Accumulated Local Effects
plot.predict_diagnostics

Plot Instance Level Residual Diagnostics
plot.predict_parts

Plot Variable Attribution Explanations
plot.model_profile

Plot Dataset Level Model Profile Explanations
model_profile

Dataset Level Variable Profile as Partial Dependence or Accumulated Local Dependence Explanations
plot.predict_profile

Plot Variable Profile Explanations
print.explainer

Print Explainer Summary
print.model_diagnostics

Print Dataset Level Model Diagnostics
theme_drwhy

DrWhy Theme for ggplot objects
predict_diagnostics

Instance Level Residual Diagnostics
predict.explainer

Predictions for the Explainer
titanic

Passengers and Crew on the RMS Titanic Data
plot.list

Plot List of Explanations
predict_parts

Instance Level Parts of the Model Predictions
yhat

Wrap Various Predict Functions
print.model_info

Print model_info
print.model_performance

Print Dataset Level Model Performance Summary
print.predict_diagnostics

Print Instance Level Residual Diagnostics
update_data

Update data of an explainer object
update_label

Update label of explainer object
colors_discrete_drwhy

DrWhy color palettes for ggplot objects
model_diagnostics

Dataset Level Model Diagnostics
loss_cross_entropy

Calculate Loss Functions
explain.default

Create Model Explainer
model_info

Exract info from model
dragons

Dragon Data
HR

Human Resources Data