Hospital rankings: a new challenge for MCDA and preference learning?

نویسنده

  • Brice Mayag
چکیده

The aim of this paper is to convince the MultiCriteria Decision Aid (MCDA) and Preference Learning communities to investigate and to contribute in the development of methodologies dedicated to hospital ranking. To do so, we present the French hospital ranking and show how these rankings can be built properly through two existing methods: decision tree and ELECTRE Tri.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Approaches for Aggregating Preferences in Participatory Forest Planning - An Experimental Study

Many forest planning situations are complex; multiple criteria of different natures have to be considered and several stakeholders or social groups may be involved. An approach that is increasingly used in these complex situations is the combination of multiple criteria decision analysis (MCDA) and participatory planning. A crucial part of MCDA processes involving more than one decision maker i...

متن کامل

Using Choquet integral in Machine Learning: what can MCDA bring?

In this paper we discuss the Choquet integral model in the realm of Preference Learning, and point out advantages of learning simultaneously partial utility functions and capacities rather than sequentially, i.e., first utility functions and then capacities or vice-versa. Moreover, we present possible interpretations of the Choquet integral model in Preference Learning based on Shapley values a...

متن کامل

Collaborative environmental planning in river management: an application of multicriteria decision analysis in the White River Watershed in Vermont.

Multicriteria decision analysis (MCDA) provides a well-established family of decision tools to aid stakeholder groups in arriving at collective decisions. MCDA can also function as a framework for the social learning process, serving as an educational aid in decision problems characterized by a high level of public participation. In this paper, the framework and results of a structured decision...

متن کامل

Labelwise versus Pairwise Decomposition in Label Ranking

Label ranking is a specific type of preference learning problem, namely the problem of learning a model that maps instances to rankings over a finite set of predefined alternatives (labels). State-of-the-art approaches to label ranking include decomposition techniques that reduce the original problem to binary classification; ranking by pairwise comparison (RPC), for example, constructs one bin...

متن کامل

Comparative analysis of SAW and TOPSIS based on interval-valued fuzzy sets: Discussions on score functions and weight constraints

Interval-valued fuzzy sets involve more uncertainties than ordinary fuzzy sets and can be used to capture imprecise or uncertain decision information in fields that require multiple-criteria decision analysis (MCDA). This paper takes the simple additive weighting (SAW) method and the technique for order preference by similarity to an ideal solution (TOPSIS) as the main structure to deal with in...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014