Analysis Of Data Using Data Mining Tool Orange
2017 IJEDR Volume 5, Issue 2 ISSN: 2321-9939Analysis of Data Using Data Mining toolOrange1Maqsud S. Kukasvadiya, 2 Dr.Nidhi H. Divecha12Research Scholar, KSV, Gandhinagar, IndiaAssistant Professor, SKPIMCS, Gandhinagar, IndiaAbstract: Data Mining is a process of computing models or design in large collection of data.There are many tools to analyze, visualize and extract data using data mining. However all thetools are not compatible to perform all analysis operations, In this paper we have attempted datamining tools for analysis however a tool is better than other.Keywords: Data Mining, orange, attribute statistics, Pre-processingI.IntroductionData Analysis is a process of performing three major operations cleansing, transformingand modeling data. However there are various tools of data mining to perform datavisualization, data analysis and data extraction. Comparison of some tools along withparameters and features and decided to use for analysis.Data Mining Tools:Orange, Weka, R, Rapid Miner, Knime, Data Melt Orange : A data mining tool which is useful for visual programming andexplorative data analysis. It can be written in Python. Orange has multiplecomponents are known as widgets. This data mining tool supportsmacOS,Windows and Linux. Weka: Weka is a machine learning data mining tool written in Java,It containsvisualization and analysis.Weka has comprehensive collection of preprocessingdata and modeling. R : R is also a data mining tool and open source. R has been used in statisticalcomputing. It implements wide variety of statistical and graphical techniques suchas linear and nonlinear Data Mining tool behaves as interpreted language. Rapid Miner:A data mining tool, It developed on an open core model. Mainlyrapid miner uses client/server model. Rapid Miner has been performed extraction,transformation and data processing operations.IJEDR1702288Internatio nal Journal of Engineering Development and Research (www.ijedr.org)1836
2017 IJEDR Volume 5, Issue 2 ISSN: 2321-9939 Knime : Knime(Konstanz Information Miner) is a open source data mining tool.Once it was using in pharmaceutical research. Data Melt : Data Melt is a framework for scientific comp utation and multiplatformand written in Java. It is open source data mining tool.Comparison of all data mining tools is with parameters. Some tools get advantageand perform better while others are not well.OffsetTrue1False0(T able-1 Specific value to set in comparison )In Table-1 and Table-2 shows all data mining tool has been specified with theirparameters either tool supports or ignore. If it gets positive or supportive value to offset assigntrue means 1 and if it gets negative or not supportive value to offset assign false means 0.Offsetis using for to balance one to another.Data Mining ToolsFeatures/Parametersof Data M ining toolsOrangeWekaRRapid M inerKnimeData MeltOpen Source111111Data Visualizationand Analysis110101Interaction and DataAnalysis110111Large Tool bo x100110Script ing Interface111011PlatformIndependence111100Covering Methods010101Parameters optimizedMethodLearn ing/Statisticalmethods000101Total060503050404(T able-2 Comparison of tools with parameters)IJEDR1702288Internatio nal Journal of Engineering Development and Research (www.ijedr.org)1837
2017 IJEDR Volume 5, Issue 2 ISSN: 2321-9939II.Methodology/TechniquesThe orange data mining is beneficial to analyze data. It supports programming languageslike C, C and Python that also supports data validation, comparison and prediction.Orange is Easy to earn. Orange tool is better than other as compare it above.Orange uses for practical Implementation: -Data Analysis:(Figure-3 Data Analysis using Orange)In Figure-3 Orange has performed practical of data analysis along with some csv(Comma Separated Values) to File Data menu tool. It co-relates with sources whichprovided to the Data Table.-Data Visualization:(Figure-4 Data Visualization using Orange)In Figure-4 Orange has performed practical of data visualization along with some csv(Comma Separated Values) to Visualize Data menu tool. It co-relates with sources whichIJEDR1702288Internatio nal Journal of Engineering Development and Research (www.ijedr.org)1838
2017 IJEDR Volume 5, Issue 2 ISSN: 2321-9939provided to the Data Table. There are attributes specified in csv file, It consists Name,Gender, Age, Race and Social Networking to represent analyze data. -Data Pre-Processing:(Figure-5 Data Visualization using Orange)III.Result:After analysis practically, orange generates results in numerical or statistical data. Itdisplay attribute statistical with mean and median values.Mean:Median:Mean value describe the age of male and female where as median display the middlevalue of data.IJEDR1702288Internatio nal Journal of Engineering Development and Research (www.ijedr.org)1839
2017 IJEDR Volume 5, Issue 2 ISSN: 2321-9939IV.Conclusion:In this study of data analysis using data mining tool, comparing their parameters to eachother and find out which tool is better to perform best analysis over data. ThereforeOrange tool has performed well and easy to use. Moreover after perform practicalimplementation Orange has done everything as its feature said. This tool makes analysiswork easier.V.References:1. Zhang, H., Raitoharju, J., Kiranyaz, S., & Gabbouj, M. (2016). Limited random walkalgorithm for big graph data clustering. Journal of Big Data, 3(1), 26.2. Pempek, Tiffany A., Yevdokiya A. Yermolayeva, and Sandra L. Calvert. "Collegestudents' social networking experiences on Facebook." Journal of applieddevelopmental psychology 30.3 (2009): 227-238.3. Griffiths, Mark D. "Facebook addiction: concerns, criticism, and recommendations—a response to Andreassen and colleagues." Psychological Reports 110.2 (2012): 518520.IJEDR1702288Internatio nal Journal of Engineering Development and Research (www.ijedr.org)1840
Knime : Knime(Konstanz Information Miner) is a open source data mining tool. Once it was using in pharmaceutical research. Data Melt : Data Melt is a framework for scientific computation and multiplatform and written in Java. It is open source data mining tool. Comparison of all data mining
Present ICE Analysis in Environmental Document 54 Scoping Activities 55 ICE Analysis Analysis 56 ICE Analysis Conclusions 57 . Presenting the ICE Analysis 59 The ICE Analysis Presentation (Other Information) 60 Typical ICE Analysis Outline 61 ICE Analysis for Categorical Exclusions (CE) 62 STAGE III: Mitigation ICE Analysis Mitigation 47 .
Traditionally, a skills gap analysis is undertaken using paper-based assessments and supporting interviews; however, technological advancements, such as skill management software, are allowing large companies to administer a skills gap analysis without using a significant proportion of human resources (Antonucci and d’Ovidio, 2012).File Size: 778KBPage Count: 24Explore furtherSkills gap analysis template - Skills for Care - Homewww.skillsforcare.org.uk40 Gap Analysis Templates & Exmaples (Word, Excel, PDF)templatelab.comConducting A Gap Analysis: A Four-Step Templatewww.clearpointstrategy.com(PDF) Gap Analysis - ResearchGatewww.researchgate.net30 FREE Gap Analysis Templates & Examples - TemplateArchivetemplatearchive.comRecommended to you b
analysis on incidents with different levels of severity e.g. 5 Whys analysis, cause-and-effect analysis, or a formal analysis using the Apollo Root Cause Analysis methodology with a cross-sectional team. Guidelines When to do a 5 Whys analysis? When to do a Cause-and-effect analysis? When to do a formal Analysis using the apollo .
Research Design: Financial Performance Analysis In this study, financial performance analysis will be used. The analysis is based on three types of analysis methods which are horizontal analysis, trend analysis and ratio analysis. All data analysis is based on the items on the financial statement. A financial statement is a written record
The Analysis Data Model Implementation Guide (ADaMIG) v1.1 defines three different types of datasets: analysis datasets, ADaM datasets, and non-ADaM analysis datasets: Analysis dataset - An analysis dataset is defined as a dataset used for analysis and reporting. ADaM dataset - An ADaM dataset is a particular type of analysis dataset that .
Module 7: Fundamental Analysis (NCFM Certification) 1. Introduction of Fundamental Analysis What is Fundamental & Technical Analysis? Difference between technical & fundamental analysis Features & benefits of Fundamental analysis 2. Top-Down Approach in Fundamental Analysis Economic Analysis Industry Analysis Company analysis 3.
Qualitative analysis, quantitative analysis, non-financial indicator analysis, financial indicator analysis, internal performance analysis, external performance analysis, project-orientated analysis, organization-orientated analysis 8 [36] Area-based Knowledge measurement in products and processes,
Oasys GSA Contents Notation 8 Degrees of freedom 10 Active degrees of freedom 10 Degrees of Freedom with no Local Stiffness 11 Analysis Options 13 Static Analysis 13 Static P-delta Analysis 13 Modal Analysis 14 Modal P-delta Analysis 14 Ritz Analysis 15 Modal Buckling Analysis 16 Model Stability Analysis 17 Non-linear Static Analysis 18
