For day-to-day decisions, multiple factors influence our choice between alternatives. Two dimensions of decision making that substantially affect choice are the objective perceptual properties of the stimulus (e.g., salience) and its subjective value. Here we measure EEGs in human subjects to relate their feedback-evoked EEG responses to estimates of prediction error given a neurally derived ex...

In many areas of medicine risk prediction models are used to identify high-risk persons to receive treatment, with the goal of maximizing the ratio of benefits to harms. Thus there is considerable interest in evaluating markers to improve risk prediction. Many measures to evaluate a new marker for risk prediction are based solely on predictive accuracy including the odds ratio, change in the ar...

We consider (prediction) markets where myopic agents sequentially interact with an automated market maker. We show a broad negative result: by varying the order of participation, the market’s aggregate prediction can converge to an arbitrary value. In other words, markets may fail to do any meaningful belief aggregation. On the positive side, we show that under a random participation model, ste...

BACKGROUND AND OBJECTIVE Prediction of intubation difficulty can save patients from major preoperative morbidity or mortality. The purpose of this paper is to assess the correlation between oro-hypo pharynx position, neck size, and length with endotracheal intubation difficulty. The study also explored the diagnostic value of Friedman Staging System in prediction cases with difficult intubation...

INTRODUCTION Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. METHODS An established...

To alleviate the high cost of main-memory accesses, computer architects have proposed various speculation mechanisms, including load-value prediction. A load-value predictor guesses the result of load instructions, thus allowing dependent instructions to execute without having to wait for the memory access to complete. Unfortunately, costly mispredictions hinder the true potential of load-value...

Various methods for value prediction have been proposed to overcome the limits imposed by data dependencies within programs. Using a value prediction scheme, an instruction's computed value is predicted during its fetch stage and forwarded to all dependent instructions to exploit parallelism. Value prediction schemes have focused on predicting the values generated by an instruction based on a l...

The evolving ease and efficiency in accessing large amounts of data presents an opportunity to execute prediction tasks based on this data (Hunt, Marin, & Stone 1964). Research in learning-from-example has addressed this opportunity with algorithms that induce either decision structures (ID3) or classification rules (AQ15). Lazy learning research on the other hand, delay the model construction ...