Classification model selection is a process of identifying a suitable model class for a given
classification task on a dataset. Traditionally, model selection is based on cross-validation, …

Classification model selection is a process of identifying a suitable model class for a given
classification task on a dataset. Traditionally, model selection is based on cross-validation, …

Identifying how hard it is to achieve a good classification performance on a given dataset
can be useful in data analysis, model selection, and meta-learning. We hypothesize that the …

Whenever a new supervised machine learning (ML) algorithm or solution is developed, it is
imperative to evaluate the predictive performance it attains for diverse datasets. This is done …

The algorithm selection problem is defined as identifying the best-performing machine
learning (ML) algorithm for a given combination of dataset, task, and evaluation measure. The …

This system represents the initial steps in the development of a water distribution and quality
monitoring system. This system is based on a wireless sensors network to detect and locate …

Wikinomics and The Wisdom of Crowds identified the phenomena of emerging social networks,
but they do not confront how businesses can profit from the wisdom of crowds. WE ARE …

The fluvial river channels dynamics are inherently spontaneous events that are influenced
by anthropogenic changes and climate variables. In order to identify channel erosion, …

This paper deals with the design of various LC oscillators around 25 GHz which can be
used for millimeter wave CMOS radios. Cross coupling is a standard technique used in …

In contrast with the past, air traffic service providers are transitioning away from radar
surveillance towards Automatic Dependant Surveillance Broadcast (ADS-B) systems to track …