Essays on Classifiers

Literature Review

Literature Review

Introduction

Machine learning techniques are based on an explicit or implicit model that enables categorize established patterns analyzed. A unique feature of these schemes is the need to train labeled data model behavior, this being a process that demands resources. Many machine learning-based schemes have been applied to NIDS. Some of the most important are Bayesian networks, Markov models, neural networks, fuzzy logic techniques, genetic algorithms, and clustering and outlier detection (Carbonneau, et. al., 2008, pp. 1140-54). The task of automatic text classification is based on building and using machines called supervised learning. The process of creating an ...

Program

Mobile devices and microblogging are emerging as significant means of spreading information during disasters not only to affected communities but also to professional responders for time-critical situational awareness (Imran et al., 2013). As the usefulness of information varies significantly, it is common for human annotators to examine the content of incoming messages and control their dissemination in a content moderation process (Link et al., 2013). The large volume, high velocity, and variety of user-generated contents from both mobile devices and social media platforms such as Twitter create a processing bottleneck in finding relevant and valuable information. With on-topic tweets being ...

Introduction

The Yurok language is a language spoken in North California. Many debates have come up during the recent years concerning the Yurok language. Yurok is much related to the Wiyot as compared to the Ritwan languages. It is important to note that Yurok is a relative although not a close one to the Algonquian languages. Additionally, the Yurok language comprises of complex verbs, and their word order is free (Native-Languages, 2015). The name ‘Yurok’ means downriver as the tribe used to reside along River Klamath in California. The number of Yurok speakers has been decreasing over the years, as there were thousands ...

Introduction

Bayesian learning basically means to get a computer to utilize information to do a task in the best possible manner. Bayesian means the optimization of deduction with limited data. The capacity to use the nervous system in times of doubt in a way close to the best shown by Bayesian statistics. Work in Machine learning refers to the use of a bunch of digits from information. Often, this word Bayesian is used in relation to neuroscience and behavioral science. The studies on these try to explain the nervous systems cognitive ability in relation to statistical settings (Helmholtz, 1962 P. 23). Many times it ...