This may tempt researchers to present their method’s performance in an over-optimistic fashion, a mechanism that is also called the “self-assessment trap” (Norel et al.
2015) constitutes a considerable external incentive for researchers to demonstrate the superiority of their new approach: journals and conferences are much more likely to accept a paper about a novel computational method if this method shows good performance and is “better” than pre-existing approaches. However, the results of such studies should be regarded with caution. Researchers who introduce a new cluster algorithm typically publish it together with a demonstration of the strengths of their approach and its superiority over alternative methods. While there already are a huge number of cluster algorithms (see e.g., Xu and Wunsch ( 2010) for an overview), researchers continue to propose novel algorithms every year. This illuminates the vital importance of strategies for avoiding the problems of over-optimism (such as, e.g., neutral benchmark studies), which we also discuss in the article.Ĭluster analysis refers to grouping similar objects in data, while separating dissimilar ones. Our study is thus a cautionary tale that illustrates how easy it can be for researchers to claim apparent “superiority” of a new cluster algorithm. Using the recently published cluster algorithm Rock as an example, we demonstrate how optimization of the used datasets or data characteristics, of the algorithm’s parameters and of the choice of the competing cluster algorithms leads to Rock’s performance appearing better than it actually is. We present an illustrative study to illuminate the mechanisms by which authors-consciously or unconsciously-paint their cluster algorithm’s performance in an over-optimistic light.
#Over optimism full
Researchers are thus often not aware of the full extent of the problem. This problem is known among many researchers, but so far, the different mechanisms leading to over-optimism in cluster algorithm evaluation have never been systematically studied and discussed.
Therefore, the superior performance of newly introduced cluster algorithms is over-optimistic and might not be confirmed in independent benchmark studies performed by neutral and unbiased authors. However, such studies are likely to be optimistically biased towards the new algorithms, as the authors have a vested interest in presenting their method as favorably as possible in order to increase their chances of getting published. If things get particularly rough, just remember, we’re all going through this together.When researchers publish new cluster algorithms, they usually demonstrate the strengths of their novel approaches by comparing the algorithms’ performance with existing competitors. Keeping the Stockdale Paradox in mind and following these strategies can help you focus during any trying time. And for those working at home, encourage your employees to turn off the computer when it’s time. Create structure and cadence for how you communicate with employees. We must learn to ruthlessly prioritize and move faster as a team. Provide mindfulness and mental health resources, and send positive social signals-actions you take to help other people feel less threatened in their day-to-day work. Give employees the time and flexibility to take care of personal needs, whether it’s accommodating childcare or illness. We have to help others stay productive with the right practices. Even try some meditation or yoga to create personal buffers-strategies to increase your sense of certainty and connection, thereby mitigating stress, and helping you to think more rationally and creatively. We all need to get proper sleep, exercise, and sustenance. Make sure to not get too far away from your routine during this time of isolation. We need to find ways to keep our brains in the best possible shape every day. To promote Stockdale’s prevailing mindset at work, use these three strategies to maintain your and your team’s focus: Take care of yourself If the leader mires in the challenges, they risk creating a culture of pessimism that will demoralize and demotivate the team, and undermine its effectiveness. If a leader ignores the challenges, the leader will appear naïve and out of touch. Although we’re not prisoners of war, we do relate to Admiral Stockdale in not knowing how long we’ll be wrestling with the challenges brought on by the COVID-19 pandemic.
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