Classical prediction methods such as Fisher's linear discriminant function were designed for small-scale problems, where the number of predictors N is much smaller than the number of observations n. Modern scientific devices often reverse this situation. A microarray analysis, for example, might include n = 100 subjects measured on N = 10,000 genes, each of which is a potential predictor. This ...

Online education platforms enable teachers to share a large number of educational resources such as questions form exercises and quizzes for students. With volumes available questions, it is important have an automated way quantify their properties intelligently select them students, enabling effective personalized learning experiences. In this work, we propose framework mining insights from at...

Conformal prediction (CP) is a wrapper around traditional machine learning models, giving coverage guarantees under the sole assumption of exchangeability; in classification problems, CP that error rate at most chosen significance level, irrespective whether underlying model misspecified. However, prohibitive computational costs full led researchers to design scalable alternatives, which alas d...

drought as a climatic phenomenon affected many different environmental issues and generally is associated with the decreasing in average precipitation. evaluation and monitoring of the drought is a fundamental step in proper programming of water resources management. regarding the recent conditions water scarcity in the urmia lake basin, assessment of the drought index in this region is inevita...

Background: The link prediction issue is one of the most widely used problems in complex network analysis. Link prediction requires knowing the background of previous link connections and combining them with available information. The link prediction local approaches with node structure objectives are fast in case of speed but are not accurate enough. On the other hand, the global link predicti...

We present a Reinforcement Learning (RL)-based model of serotonin which tries to reconcile some of the diverse roles of the neuromodulator. The proposed model uses a novel formulation of utility function, which is a weighted sum of the traditional value function and the risk function. Serotonin is represented by the weightage, α, used in this combination. The model is applied to three different...