Ham or spam? A comparative study for some content-based classification algorithms for email filtering

2014 ◽  
Author(s):  
Salwa Adriana Saab ◽  
Nicholas Mitri ◽  
Mariette Awad
Keyword(s):  
Comparative Study ◽  
Classification Algorithms ◽  
Email Filtering

scholarly journals Predicting the Demand for Fmcg using Machine Learning

2021 ◽  
Vol 10 (3) ◽  
pp. 169-171
Author(s):  
Anish Mebal. P ◽  
Hema. S ◽  
Jothika. S.J ◽  
Manochitra M
Keyword(s):  
Machine Learning ◽  
Comparative Study ◽  
Consumer Goods ◽  
Fast Moving ◽  
Statistical Information ◽  
Classification Algorithms ◽  
Perishable Products ◽  
Fresh Food ◽  
Fast Moving Consumer Goods ◽  
Competitive Factor

Now-a-days the more accurate prediction of the demand for fast-moving consumer goods (FMCG) is a competitive factor for both the manufacturers and retailers, especially in the super markets, wholesale manufacturers and fresh food sectors and other consumable industries. This proposed system presents the benefits of Machine Learning in sales forecasting for short shelf-life and highly-perishable products, as it predict the statistical information as a result, improves inventory balancing throughout the chain, improving availability to consumers and increasing profitability. This performance is done with various classification algorithms and comparative study is done with some metrics like accuracy, precision, recall and f-score. So that it helps in finding customer need and to increase the profit of the manufacturers

scholarly journals The State-of-the-Art Technology of Currency Identification

2017 ◽  
Vol 9 (3) ◽  
pp. 58-72 ◽  
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

The State-of-the-Art Technology of Currency Identification

2018 ◽  
pp. 252-269
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

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