scholarly journals The Impact of Feature Extraction on the Performance of a Classifier: kNN, Naïve Bayes and C4.5

2005 ◽  
pp. 268-279 ◽  
Author(s):  
Mykola Pechenizkiy
Keyword(s):  
Feature Extraction ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
The Impact

scholarly journals Twitter based Sentiment Analysis of Impact of Covid-19 on Education Globaly

2021 ◽  
Vol 12 (03) ◽  
pp. 15-24
Author(s):  
Swetha Sree Cheeti ◽  
Yanyan Li ◽  
Ahmad Hadaegh
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Education System ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Naive Bayes Classifier ◽  
Bayes Classifier ◽  
Naïve Bayes Classifier ◽  
The World ◽  
The Impact

Education system has been gravely affected due to widespread of Covid-19 across the globe. In this paper we present a thorough sentiment analysis of tweets related to education available on twitter platform and deduce conclusions about its impact on people’s emotions as the pandemic advanced over the months. Through twitter over ninety thousand tweets have been gathered related to the circumstances involving the change in education system over the world. Using Natural language tool kit (NLTK) functionalities and Naive Bayes Classifier a sentiment analysis has been performed on the gathered dataset. Based on the results of this analysis we infer to exhibit the impact of covid-19 on education and how people’s sentiment altered due to the changes with regard to the education system. Thus, we would like to present a better understanding of people’s sentiment on education while trying to cope with the pandemic in such unprecedented times.

scholarly journals Out of Control: Growth and Indirect Discrimination in Ada and Canyon Counties' Rental Processes

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Berit Schaus ◽  
Sharon Hanson ◽  
Timothy Thomas
Keyword(s):  
Naive Bayes ◽  
Housing Prices ◽  
Naïve Bayes ◽  
Bayes Model ◽  
Control Growth ◽  
Indirect Discrimination ◽  
Geographical Regions ◽  
Naïve Bayes Model ◽  
The Impact ◽  
Minimal Research

Minimal research has been done on race in evictions and the rental process, and those studies that have been performed have been limited to narrow geographical regions (Thomas, 2017; Desmond, 2016). Additionally, research hasn’t been extended to Idaho, a state that is recognized for its rapid population growth. Research on evictions’ impact on New Americans is essentially nonexistent. Employing the Naïve Bayes Model, a modification of the Naïve Bayes Model, and content analysis of interviews, this study sought to uncover the impact of racial discrimination and growth in the eviction process. The results proved that black and Latinx minorities are evicted at higher rates than their white and Asian counterparts and that a lack of tenant protections and rapidly increasing housing prices, among other things, have played pivotal roles in Idaho’s eviction rates, specifically of racial minorities.

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