Comparative Analysis of Classification Techniques in Data Mining Using Different Datasets
نویسندگان
چکیده
Data mining is the invention of knowledge and useful information from the large amounts of data stored in databases. It is referred as an analysis study of the Knowledge discovery in database process or KDD. Data mining tools are used in forecasting future trends and behaviours, allowing businesses to make proactive, knowledge-driven decisions. Classification is an important data mining technique with broad applications. It classifies data of different kinds. Classification is used in every field of our life. Classification is used to classify each item in a set of data into one of predefined group of classes. The present study aimed to do the comparative analysis of several data mining classification techniques on the basis of parameters accuracy, execution time, types of datasets and applications. Several major kinds of classification techniques are present, the main concerned of this work on decision tree based (M5P), nearest neighbour based (K star), rule-based (M5 Rule), neural network based (Multilayer Perceptron).
منابع مشابه
A Comparative Study of SVM and RF Methods for Classification of Alteration Zones Using Remotely Sensed Data
Identification and mapping of the significant alterations are the main objectives of the exploration geochemical surveys. The field study is time-consuming and costly to produce the classified maps. Therefore, the processing of remotely sensed data, which provide timely and multi-band (multi-layer) data, can be substituted for the field study. In this study, the ASTER imagery is used for altera...
متن کاملPerformance Analysis of Different Classification Methods in Data Mining for Diabetes Dataset Using WEKA Tool
Data mining is the process of analyzing data based on different perspectives and summarizing it into useful information. Classification is one of the generally used techniques in medical data mining. The goal here is to discover new patterns to provide meaningful and useful information for the users. Recently data mining techniques are applied to healthcare datasets to explore suitable methods ...
متن کاملPrediction of Student Learning Styles using Data Mining Techniques
This paper focuses on the prediction of student learning styles using data mining techniques within their institutions. This prediction was aimed at finding out how different learning styles are achieved within learning environments which are specifically influenced by already existing factors. These learning styles, have been affected by different factors that are mainly engraved and found wit...
متن کاملA Comparative Analysis of Various Clustering Techniques on Random Datasets
ata Mining is a discovery of knowledge used basically used for finding or exploring the new facts among datasets. It allows the user to find the hidden data among available datasets. Data mining consists of various components including clustering, classification, association rules, sequence analysis etc. Unlabeled data are becoming common and mining such databases becomes more challenging. Clus...
متن کاملCustomer Behavior Mining Framework (CBMF) using clustering and classification techniques
The present study proposes a Customer Behavior Mining Framework on the basis of data mining techniques in a telecom company. This framework takes into account the customers’ behavior patterns and predicts the way they may act in the future. Firstly, clustering technique is used to implement portfolio analysis and previous customers are divided based on socio-demographic features using k</em...
متن کامل