Install
User Guide
API
Examples
Toggle Menu
User Guide
1. Introduction
2. Data Pipeline
2.1. Data Load
2.2. Data Summary
2.3. Data Preparation
2.4. Exploratory Analysis
2.5. Data Quality (Integrity Check)
2.6. Data Quality (Outlier Detection)
2.7. Data Quality (Drift Test)
2.8. Feature Selection
3. Model Train and Tune
4. Post-hoc Explainability
5. Interpretable Models
6. Diagnostic Suite
7. Model Comparison
8. Case Studies
2.
Data Pipeline
¶
2.1. Data Load
2.1.1. Built-in Dataset
2.1.2. External Dataset (csv files)
2.1.3. External Dataset (Spark file)
2.1.4. Examples
2.2. Data Summary
2.2.1. Summary Statistics
2.2.2. Feature Manipulation
2.2.3. Examples
2.3. Data Preparation
2.3.1. Basic Settings
2.3.2. Train-test Splits
2.3.3. Examples
2.4. Exploratory Analysis
2.4.1. Univariate Plots
2.4.2. Bivariate Plots
2.4.3. Multivariate Plots
2.4.4. Examples
2.5. Data Quality (Integrity Check)
2.5.1. Single-column Checks
2.5.2. Duplicated Samples
2.5.3. Highly correlated features
2.5.4. Examples
2.6. Data Quality (Outlier Detection)
2.6.1. Methodology
2.6.2. Analysis and Comparison
2.6.3. Examples
2.7. Data Quality (Drift Test)
2.7.1. Marginal Distribution Drift
2.7.2. Energy Distance
2.7.3. Examples
2.8. Feature Selection
2.8.1. Correlations
2.8.2. Distance Correlation
2.8.3. Use of Feature Importance
2.8.4. Randomized Conditional Independence Test
2.8.5. Examples
