• Predictive Accuracy Measures. These measures evaluate how close the recommender system came to predicting actual rating/utility values. • Classification Accuracy Measures. These measures evaluate the frequency with which a recommender system makes correct/incorrect decisions regarding items. • Rank Accuracy Measures. These measures evaluate the correctness of the ordering of items performed b...

An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of me...

Particle tracking techniques are often used to assess the local mechanical properties of cells and biological fluids. The extracted trajectories are exploited to compute the mean-squared displacement that characterizes the dynamics of the probe particles. Limited spatial resolution and statistical uncertainty are the limiting factors that alter the accuracy of the mean-squared displacement esti...

Because of a lack of a priori information, the minimum mean-squared error predictor, the conditional expectation, is often not known for a non-Gaussian time series. We show that the nonparametric kernel regression estimator of the conditional expectation is mean-squared consistent for a time series: When used as a predictor, the estimator asymptotically matches the mean-squared error produced b...