Examples

Data Pipeline

Data Load (Built-in Dataset)

Data Load (Built-in Dataset)

Data Load (Pandas DataFrame)

Data Load (Pandas DataFrame)

Data Load (Spark)

Data Load (Spark)

Data Summary

Data Summary

EDA

EDA

Data Preparation

Data Preparation

Data Quality Check

Data Quality Check

Feature Selection

Feature Selection

Model Train and Tune

Train Models

Train Models

HPO - Grid Search

HPO - Grid Search

HPO - Random Search

HPO - Random Search

Register sklearn Style Models

Register sklearn Style Models

Register H2O Models

Register H2O Models

Register Arbitrary Models

Register Arbitrary Models

Register PySpark Models

Register PySpark Models

Post hoc Explainability

Permutation Feature Importance

Permutation Feature Importance

Partial Dependence Plot

Partial Dependence Plot

H-statistics

H-statistics

Individual Conditional Expectation

Individual Conditional Expectation

Accumulated Local Effects

Accumulated Local Effects

Local Interpretable Model-Agnostic Explanation

Local Interpretable Model-Agnostic Explanation

SHapley Additive exPlanations

SHapley Additive exPlanations

Data Dependent Explanation

Data Dependent Explanation

Interpretable Models

GLM Logistic Regression (Taiwan Credit)

GLM Logistic Regression (Taiwan Credit)

GLM Linear Regression (Bike Sharing)

GLM Linear Regression (Bike Sharing)

GAM Classification (CoCircles)

GAM Classification (CoCircles)

GAM Regression (California Housing)

GAM Regression (California Housing)

Tree Classification (TaiwanCredit)

Tree Classification (TaiwanCredit)

Tree Regression (California Housing)

Tree Regression (California Housing)

FIGS Classification (Taiwan Credit)

FIGS Classification (Taiwan Credit)

FIGS Regression (California Housing)

FIGS Regression (California Housing)

XGB-1 Classification (CoCircles)

XGB-1 Classification (CoCircles)

XGB-1 Regression (California Housing)

XGB-1 Regression (California Housing)

XGB-2 Classification (Taiwan Credit)

XGB-2 Classification (Taiwan Credit)

XGB-2 Regression (Bike Sharing)

XGB-2 Regression (Bike Sharing)

EBM Classification (Taiwan Credit)

EBM Classification (Taiwan Credit)

EBM Regression (Bike Sharing)

EBM Regression (Bike Sharing)

GAMI-Net Classification (Taiwan Credit)

GAMI-Net Classification (Taiwan Credit)

GAMI-Net Regression (Bike Sharing)

GAMI-Net Regression (Bike Sharing)

ReLU DNN Classification (Taiwan Credit)

ReLU DNN Classification (Taiwan Credit)

ReLU DNN Regression (Friedman)

ReLU DNN Regression (Friedman)

Outcome Testing

Accuracy: Classification

Accuracy: Classification

Accuracy: Regression

Accuracy: Regression

WeakSpot: Classification

WeakSpot: Classification

WeakSpot: Regression

WeakSpot: Regression

Overfit: Classification

Overfit: Classification

Overfit: Regression

Overfit: Regression

Reliability: Classification

Reliability: Classification

Reliability: Regression

Reliability: Regression

Robustness: Classification

Robustness: Classification

Robustness: Regression

Robustness: Regression

Resilience: Classification

Resilience: Classification

Resilience - Regression

Resilience - Regression

Fairness Test: XGB2

Fairness Test: XGB2

Segmented Diagnose (Classification)

Segmented Diagnose (Classification)

Segmented Diagnose (Regression)

Segmented Diagnose (Regression)

Scored Test: Classification

Scored Test: Classification

Scored Test: Regression

Scored Test: Regression

Model Comparison

Model Comparison: Classification

Model Comparison: Classification

Model Comparison: Regression

Model Comparison: Regression

Fairness Comparison

Fairness Comparison

Build Robust Models with Monotonicity Constraints

Build Robust Models with Monotonicity Constraints