5.4 Decision Tree Interpretable Machine Learning

Machine learning algorithms usually operate as black boxes and it is unclear how they derived a certain decision. This book is a guide for practitioners to make machine learning decisions interpretable.

Examining influential factors for acknowledgements classification

Interpretable Ensemble-Machine-Learning models for predicting creep behavior of concrete - ScienceDirect

Interpretable Machine Learning

PPT - Lecture 5 Machine Learning 第 5 讲 机器学习 PowerPoint Presentation - ID:5148268

A branch & bound algorithm to determine optimal bivariate splits for oblique decision tree induction

Examining influential factors for acknowledgements classification

[Molnar, Christoph] on . *FREE* shipping on qualifying offers. Interpretable Machine Learning: A Guide For Making Black Box Models

Interpretable Machine Learning: A Guide For Making Black Box Models Explainable

Symmetry, Free Full-Text

Interpretable Machine Learning

Interpretable Machine… by Christoph Molnar [PDF/iPad/Kindle]

8.7 Prototypes and Criticisms Interpretable Machine Learning

Number of ways to traverse an N-ary tree - GeeksforGeeks

Complete N-ary Trees

Explore - LeetCode

6.13 From constituency to tree diagrams – Essentials of Linguistics, 2nd edition

The Sibley Guide to Trees (Sibley Guides): Sibley, David Allen: 9780375415197: : Books