Selecting Classification and Clustering Tools for Academic Support
نویسنده
چکیده
Classification and clustering are powerful and popular data mining techniques. Organizations use them to capture information, retain customers, and improve business performance. This paper presents a method for selecting data mining software for an academic environment based on its classification and clustering tools. This research applies the data mining software evaluation framework to evaluate three major commercial data mining software: SAS Enterprise Miner, Clementine from SPSS, and IBM DB2 Intelligent Miner. We added to the framework a criterion that became important in the Internet age. After ranking software on relevant criteria in the framework then purchase the best one that is affordable for academic support.
منابع مشابه
Improving the Operation of Text Categorization Systems with Selecting Proper Features Based on PSO-LA
With the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. One of the major problems in text classification relates to the high dimensional feature spaces. Therefore, the main goal of text classification is to reduce the dimensionality of features space. There are many feature selection methods. However...
متن کاملAsthma Control Level Assessment by Moving from the Current Reactive Care Models into a Preventive Approach based on Fuzzy Clustering and Classification Algorithms
Background and Aim: Asthma is a common and chronic disease of respiratory tracts. The best way to treat Asthma is to control it. Experts of this field suggest the continues monitoring on Asthma symptoms and adjustment of self-care plan with offering the preventive treatment program to have desired control over Asthma. Presenting these plans by the physician is set based on the control level in ...
متن کاملFeature Selection and Classification of Microarray Gene Expression Data of Ovarian Carcinoma Patients using Weighted Voting Support Vector Machine
We can reach by DNA microarray gene expression to such wealth of information with thousands of variables (genes). Analysis of this information can show genetic reasons of disease and tumor differences. In this study we try to reduce high-dimensional data by statistical method to select valuable genes with high impact as biomarkers and then classify ovarian tumor based on gene expression data of...
متن کاملAn Improvement in Support Vector Machines Algorithm with Imperialism Competitive Algorithm for Text Documents Classification
Due to the exponential growth of electronic texts, their organization and management requires a tool to provide information and data in search of users in the shortest possible time. Thus, classification methods have become very important in recent years. In natural language processing and especially text processing, one of the most basic tasks is automatic text classification. Moreover, text ...
متن کاملCredit scoring in banks and financial institutions via data mining techniques: A literature review
This paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in Credit scoring. Yet there isn’t any literature in the field of data mining applications in credit scoring. Using a novel research approach, this paper investigates academic and systematic literature review and includes all of the journals in the Science direct onli...
متن کامل