Analysis Guides

This section contains comprehensive guides for using tab-right’s analysis capabilities. These guides provide step-by-step examples and best practices for different types of data analysis tasks.

Analysis Guides

• Drift Detection
  • Drift Detection with tab-right
  • Available Drift Metrics
  • Example: Using DriftCalculator and DriftPlotter
  • Feature-Level Distribution Comparison
  • Categorical Feature Visualization
  • Direct Functions API
  • Working with Multiple Drift Metrics
  • Visualizing Different Types of Drift
  • Key Features of tab-right’s Drift Detection
• Segmentation Calculation
  • What is Segmentation Analysis?
  • Using tab-right for Segmentation Analysis
  • Basic Usage
  • Working with Actual Data
  • Visualization with Higher-is-Better Metrics
  • Interactive Visualization with Plotly
  • Key Steps for Segmentation Analysis
  • Key Benefits of Using tab-right for Segmentation
• Double Segmentation
  • What is Double Segmentation?
  • Tab-right’s Double Segmentation Tools
  • Basic Usage with Continuous Features
  • Working with Categorical Features
  • Mixed Categorical and Continuous Features
  • Interactive Visualization with Plotly
  • Using Different Metrics
  • Key Features of Double Segmentation

Guide Overview

Drift Detection

Learn how to detect and visualize data drift between reference and current datasets using tab-right’s comprehensive drift detection tools.

Segmentation Calculation

Understand how to perform segmentation analysis to evaluate model performance across different subsets of your data.

Double Segmentation

Explore advanced segmentation techniques that analyze model performance across combinations of two features to identify complex patterns and interactions.

Each guide includes practical examples, code samples, and visualization techniques to help you get the most out of tab-right’s analysis capabilities.