This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Add value with every decision using a simple yet powerful framework Few things are as valuable in business, and in life, as the ability to make good decisions. Can you imagine how much more rewarding your life and your business would be if every decision you made were the best it could be? Decision Quality empowers you to make the best possible choice and get more of what you truly want from every decision. Dr. Carl Spetzler is a leader in the field of decision science and has worked with organizations across industries to improve their decision-making capabilities. He and his co-authors, all experienced consultants and educators in this field, show you how to frame a problem or opportunity, create a set of attractive alternatives, identify relevant uncertain information, clarify the values that are important in the decision, apply tools of analysis, and develop buy-in among stakeholders. Their straightforward approach is elegantly simple, yet practical and powerful. It can be applied to all types of decisions. Our business and our personal lives are marked by a stream of decisions. Some are small. Some are large. Some are life-altering or strategic. How well we make those decisions truly matters. This book gives you a framework and thinking tools that will help you to improve the odds of getting more of what you value from every choice. You will learn: The six requirements for decision quality, and how to apply them The difference between a good decision and a good outcome Why a decision can only be as good as the best of the available alternatives Methods for making both "significant" and strategic decisions The mental traps that undermine decision quality and how to avoid them How to deal with uncertainty—a factor in every important choice How to judge the quality of a decision at the time you're making it How organizations have benefited from building quality into their decisions. Many people are satisfied with 'good enough' when making important decisions. This book provides a method that will take you and your co-workers beyond 'good enough' to true Decision Quality.