(PDF) Data mining techniques and applications

17 Pages1315 Words150 Views

Added on 2021-04-24

(PDF) Data mining techniques and applications

Added on 2021-04-24

BookmarkRelated Documents

Running head: DATA MINING-2Data Mining-2Name of StudentName of UniversityCourse ID

(PDF) Data mining techniques and applications_1

DATA MINING-21Table of ContentsIntroduction:....................................................................................................................................2Discussion:.......................................................................................................................................2Task 1:.............................................................................................................................................2Task 2:.............................................................................................................................................3Conclusion:....................................................................................................................................15References:....................................................................................................................................16

(PDF) Data mining techniques and applications_2

DATA MINING-22Introduction:The assignment in the first part discusses about the security, privacy and ethics of datamining. The two research articles are provided in the assignment file that would help to describethe limited utility and impractical scientific knowledge. The dynamic association between humanrights and big data is discussed in the discussion section.On the other hand, the second part of the assignment file takes into account the analysisby “Weka” software. The marks of assignments and final exam are analysed with summarystatistics and necessary visualizations. Besides, the basic activities like handling the missingvalues are executed in the second part. Discussion:Task 1:Topic: Security, Privacy and Ethics in Data Mining.As more as the personal data is being gathered, the most powerful computers are beingcollected according to the availability of the legitimate and abusive usage. There are many inter-associated aspects to the digital revolution that has enhanced capabilities of storing the data andmodels applied for producing knowledge. Big data is the area to criminal curriculum andprovocation. Big data is majorly used in public health sector, bio-chemical research sector,property dealing and insurance sector (Tasioulas, 2016). The emergence of big data is anexample of scientific and technological innovative generator that includes enormous potentialbenefits and market risks. The heightened security of big data can sometimes degrade the level of privacy. The lawenforcement agencies gather data that could be treated as terrorist or potential customers.Business companies aim to deliver targeted advertising and track the online strategy.Organisations like Google, Apple and Amazon takes care about more intelligence and decryptedversion of data. The counter measures of internet theft and cyber crime are auditing andcorporate methods, encryption, control over data access, backups and detection of intrusion. Datacontrol and data incorporation with the help of sophisticated software of the business authoritieshave reduced vulnerability of the dataset (Ryoo, 2016). Transparency in security and privacy is the vital factor to address the security and privacyissues. Big data handlers expose data who can access and grant it. The business organisationsmay achieve public trust by providing security controls to protect big scale data. Ethics in big data handling enterprises improves health and health resources. Big dataanalysis pursues self-interest defining satisfactory curiosity and career advancement. Demand ofconsumers drives security and privacy that is critical to a highlighted level of security throughvehicles. Particularly, the confronting towards the enhancement with dogmatic understanding ofhuman right became unresponsive towards the changing circumstances that lead to rights toprivacy and authenticity.

(PDF) Data mining techniques and applications_3

DATA MINING-23Task 2:Text editor and “Arff” file creation: Summary statistics and histograms:Table 1: Summary statistics table of marks of Assignment-1The summary statistics of assignment 1 indicates that lowest mark in assignment 1 is 30 andhighest mark is 84. The average mark of assignment 1 is 49.103 and standard deviation is 13.28.Figure 1: Histogram of marks of Assignment-1

(PDF) Data mining techniques and applications_4

End of preview

Want to access all the pages? Upload your documents or become a member.

ITC 516- Data Mining and Visualization | Assignment

|10

|2381

|40

ITC516 - Data Mining and Visualization

|1954

|101

Data Mining and Visualization: Business, Security, Privacy, and Ethics

|1967

|462

Data Mining in Business 8 DATA MINING IN BUSINESS

|10

|2116

|84

Information Technology Ethics - Violation of Privacy, Intellectual Property Rights and Whistleblowing

|1935

|378

ITC516

|11

|1113

|267

(PDF) Data mining techniques and applications