Two-way Decision Research Articles

Three-way decisions based software defect prediction

Based on a two-stage classification method and a two-stage ranking method on three-way decisions, this paper introduces a three-way decisions framework for cost-sensitive software defect prediction. For the classification problem in software defect prediction, traditional two-way decisions methods usually generate a higher classification error and more decision cost. Here, a two-stage classification method that integrates three-way decisions and ensemble learning to predict software defect is proposed. Experimental results on NASA data sets show that our method can obtain a higher accuracy and a lower decision cost. For the ranking problem in software defect prediction, a two-stage ranking method is introduced. In the first stage, all software modules are classified into three different regions based on three-way decisions. A dominance relation rough set based ranking algorithm is next applied to rank the modules in each region. Comparison experiments with 6 other ranking methods present that our proposed method can obtain a better result on FPA measure.

Exploring Ethical Leadership

Brown (2007) has described ethical leadership as “the demonstration of normatively appropriate conduct through personal actions and interpersonal relationships, and the promotion of such conduct to followers through two-way communication, reinforcement, and decision making” (p. 141). Kanungo (2001) has noted that “ethical leaders engage in acts and behaviors that benefit others, and at the same time, they refrain from behaviors that can cause any harm to others” (cited in Yukl, Mahsud, Hassan, & Prussia, 2013, p. 38). This paper explores the topic of ethical leadership. It investigates the following questions: What is ethical leadership? What is ethical leadership behavior? What is unethical leadership behavior? What are the benefits of ethical behavior? What are the characteristics of an ethical leader? What misconceptions about ethical leadership exist? What mistakes must leaders avoid to ensure sound business ethics? How is ethical leadership sustained - how do organizations promote ethical leadership?

Three-way decisions space and three-way decisions

Ideas of three-way decisions proposed by Yao come from rough sets. It is well known that there are three basic elements in three-way decisions theory, which are ordered set as to define three regions, object set contained in evaluation function and evaluation function to make three-way decisions. In this paper these three basic elements are called decision measurement, decision condition and evaluation function, respectively. In connection with the three basic elements this paper completes three aspects of work. The first one is to introduce axiomatic definitions for decision measurement, decision condition and evaluation function; the second is to establish three-way decisions space; and the third is to give a variety of three-way decisions on three-way decisions spaces. Existing three-way decisions are the special examples of three-way decisions spaces defined in this paper, such as three-way decisions based on fuzzy sets, random sets and rough sets etc. At the same time, multi-granulation three-way decisions space and its corresponding multi-granulation three-way decisions are also established. Finally this paper introduces novel dynamic two-way decisions and dynamic three-way decisions based on three-way decisions spaces and three-way decisions with a pair of evaluation functions.

A Multifaceted Analysis of Probabilistic Three-way Decisions

In situations where available information or evidence is incomplete or uncertain, probabilistic two-way decisions/classifications with a single threshold on probabilities for making either an acceptance or a rejection decision may be inappropriate. With the introduction of a third non-commitment option, probabilistic three-way decisions use a pair of thresholds and provide an effective and practical decision-making strategy. This paper presents a multifaceted analysis of probabilistic three-way decisions. By identifying an inadequacy of two-way decisions with respect to controlling the levels of various decision errors, we examine the motivations and advantages of three-way decisions. We present a general framework for computing the required thresholds of a three-way decision model as an optimization problem. We investigate two special cases, one is a decision-theoretic rough set model and the other is an information-theoretic rough set model. Finally, we propose a heuristic algorithm for finding the required thresholds.

Watching Genes Loop the Loop

Watching Genes Loop the Loop

The superiority of three-way decisions in probabilistic rough set models

Three-way decisions provide a means for trading off different types of classification error in order to obtain a minimum cost ternary classifier. This paper compares probabilistic three-way decisions, probabilistic two-way decisions, and qualitative three-way decisions of the standard rough set model. It is shown that, under certain conditions when considering the costs of different types of miss-classifications, probabilistic three-way decisions are superior to the other two.

Thresholds and optimal binary comparison search trees

We present an O( n 4)-time algorithm for the following problem: Given a set of items with known access frequencies, find the optimal binary search tree under the realistic assumption that each comparison can only result in a two-way decision: either an equality comparison or a less-than comparisons. This improves the best known result of O( n 5) time, which is based on split tree algorithms. Our algorithm relies on establishing thresholds on the frequency of an item that can occur as an equality comparison at the root of an optimal tree.

Discussion

Smart city construction has penetrated all aspects of human life. People can continue to feel the convenience of life brought by new technologies and new services. In order to further optimize the smart city system, aiming at the sparsity of scoring data and the difficulty of two-way decisions to deal with uncertain decisions in the recommendation algorithm, a three-way Naive Bayesian Collaborative Filtering Recommendation model (3NBCFR) for smart city is constructed by integrating Naive Bayesian, three-way decisions and collaborative filtering algorithm. Firstly, we consider the influence of item attributes on user scoring. Naive Bayesian classifier is used to score unrated items, which can effectively fill in the missing values in the score matrix and solve the problem of data sparsity. Secondly, to ensure sustainable recommendations for uncertain goals, the three-way decisions is introduced into the collaborative filtering recommendation system, three-way recommendation rules are formulated, and 3NBCFR is constructed. Finally, the model is applied to the movie recommendation system. The experiment on Movielens shows that compared with the traditional collaborative filtering recommendation algorithm, 3NBCFR algorithm reduces the recommendation cost and improves the recommendation quality. At the same time, it lays a foundation for promoting the construction of smart city.