A Survey on Major Classification Algorithms and Comparative Analysis of Few Classification Algorithms on Contact Lenses Data Set Using Data Mining Tool

Author(s):  
Syed Nawaz Pasha ◽  
D. Ramesh ◽  
Mohammad Sallauddin
2013 ◽  
Vol 433-435 ◽  
pp. 1885-1889
Author(s):  
Lu Feng ◽  
Zhan Quan Wen ◽  
Jie Mei Lin

We used the principle of hyperlink analysis method to mine the website data according to the indicators of the hyperlink analysis. We selected Taobao.com as an object of study. The evaluation indicators of network marketing effect were page views, sales quantity, sales, the number of adding store to bookmark . According to our research, we find Taobao.com stores can use data mining tool to obtain the very good marketing effect.


Basic management and understanding the conducted of the client has turned out to be indispensable and testing issue for associations to continue their situation in the focused markets. Mechanical advancements have cleared leap forward in quicker handling of questions and sub-second reaction time. Information mining devices have turned out to be surest weapon for breaking down colossal measure of information and leap forward in settling on right choices. The target of this paper is to break down the colossal measure of information subsequently abusing the buyer conduct and settle on the right choice prompting aggressive edge over adversaries. Test investigation has been done utilizing affiliation principles utilizing Market Basket examination toward demonstrate its value more the regular systems.


2017 ◽  
Vol 10 (04) ◽  
pp. 788-792 ◽  
Author(s):  
D. Ramesh ◽  
Syed Pasha ◽  
G Roopa

Data mining has become one of the emerging fields in research because of its vast contents. Data mining is used for finding hidden patterns in the database or any other information repository. This information is necessary to generate knowledge from the patterns. The main task is to extract knowledge out of the information. In this paper we use a data mining technique called classification to determine the playing condition based on the current temperature values. Classification technique is a powerful way to classify the attributes of the dataset into different classes. In our approach we use classification algorithms like Decision Tree (J48), REP Tree and Random Tree. Then we compare the efficiencies of these classification algorithms. The tool we use for this approach is WEKA (Waikato Environment for Knowledge Analysis) a collection of open source machine learning algorithms.


Author(s):  
Nur’Ain Maulat Samsudin ◽  
Cik Feresa binti Mohd Foozy ◽  
Nabilah Alias ◽  
Palaniappan Shamala ◽  
Nur Fadzilah Othman ◽  
...  

YouTube has become a popular social media among the users. Due to YouTube popularity, it became a platform for spammer to distribute spam through the comments on YouTube. This has become a concern because spam can lead to phishing attack which the target can be any user that click any malicious link. Spam has its own features that can be analyzed and detected by classification. Hence, enhancement features are proposed to detect YouTube spam. In order to conduct the experiments, a YouTube Spam detection framework that consists of five (5) phases such as data collection, pre-processing, features selection and extraction, classification and detection were developed. This paper, proposed the YouTube detection framework, examined and validate each of the phases by using two types of data mining tool. The features are constructed from analysis by using data collected from YouTube Spam dataset by using Naïve Bayes and Logistic Regression and tested in two different data mining tools which is Weka and Rapid Miner. From the analysis, thirteen (13) features that had been tested on Weka and RapidMiner shows high accuracy, hence is being used throughout the experiment in this research. Result of Naïve Bayes and Logistic Regression run in Weka is slightly higher than RapidMiner. In addition, result of Naïve Bayes is higher than Logistic Regression with 87.21% and 85.29% respectively in Weka. While in RapidMiner there is slightly different of accuracy between Naïve Bayes and Logistic Regression 80.41% and 80.88%. But, precision of Naïve Bayes is higher than Logistic Regression.


Sign in / Sign up

Export Citation Format

Share Document