March 26, 2022

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA COMMUNICATIONS MDCN 5102: EMERGING TECHNOLOGIES IN ICT ORDINARY EXAMINATIONS DATE: MAY, 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take-Home Examination (THE) QUESTION ONE (50 MARKS) Background to Assignment In the recent years, there has been a unprecedented growth in data and computing power which has in turn fuelled the advancement of data-driven technologies such as Artificial Intelligence (AI). As with any other technology there are the good and bad sides of AI. It can be used to foster economic growth and support better quality of life but at same time there are emerging ethical, legal and governance challenges to it. One may ask number of questions regarding Kenya’s preparedness in handling AI. For example, is there an existing legal framework in Kenya address issues of privacy, data protection and ethics in Emerging ICTs? Or if lacking, then is there need for new legislation, codes of conduct etc. to deal with privacy impacts not covered by the existing framework? You will develop a paper outlining a model AI framework for Kenya. You will undertake an extensive literature review and benchmarking with other countries that have one. You will be required to critically analyse the literature gathered from the benchmarking exercise bearing in mind that models vary from region to region and taking account of the economic variations of nations. Questions In your model, ensure that you have addressed the following issues; 1. Articulate a new set of ethical principles for AI in Kenya. Keep in mind that there is a variation of these principles across cultures, jurisdictions and industry sectors. 2. Address issues around data sharing. It could be between the public and private sectors or between or within organisations. 3. Discuss issues relating to the legal liabilities associated with AI in Kenya. These may include, intellectual property rights, and societal impacts of AI. Further Instructions • Ensure that you provide a list of references for all resources used • Plagiarism will result in cancellation of results and student will be subjected to the universities disciplinary process • Student may be requested to substantiate aspect of your paper when deemed necessary • Use the APA style (50 Marks)

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA COMMUNICATIONS MDC 6101 – COMPUTER NETWORKS DATE: MAY, 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take Home Examination (THE) QUESTION ONE (50 MARKS) 1. Discuss ANY THREE modern computer network challenges which researchers are concentrating on in the recent times (from 2018 onwards) 2. Discuss the way forward on those challenges identified in (1) from a researcher’s point of view. NB: i. The Assignment should have the following sections: a. Title b. Abstract c. Introduction d. Literature Review – identifying and discussing the challenges e. Way Forward f. References ii. Your work should include latest citations using the APA referencing style iii. Plagiarism will attract a heavy penalty – including a cancellation of the entire work a. Avoid copying and pasting – read the source, understand and then rephrase b. Your work will undergo anti-plagiarism test to confirm its genuineness c. You may do the anti-plagiarism before you submit your work

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYICS MDA 5404: DATA ANALYTICS AND KNOWLEDGE ENGINEERING DATE: MAY 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take Home Examination (THE) QUESTION ONE Corona Virus Disease 2019(COVID-19) outbreak was first reported in Wuhan, China and has spread to more than 50 countries. WHO declared COVID-19 as a Public Health Emergency of International Concern (PHEIC) on 30 January 2020. Naturally, a rising infectious disease involves fast spreading, endangering the health of large numbers of people, and thus requires immediate actions to prevent the disease at the community level. Requirement -As an attempt to address this problem, use any publicly available data and write a research paper that proposes a predictive model that can be used in Kenya or in specific Kenyan counties to predict any of the following cases: i. Number of confirmed cases ii. Number of Recoveries iii. Number of Deaths – Submit a Zip file that consist Downloaded data, Research paper and a document with screen shots of python code and output – The paper should be structured as follows: 1. Front Pages (3 Marks) – Title page, Glossary, acronyms, Abstract and table of content 3. Introduction (10 Marks) – Background of convid-19 and predictive analytics – Problem statement – Objectives -Significance of the study 4. Literature Review (10 Marks) – Review of at least three studies that have used algorithms that have been used by other researchers perform predicting analytics in COVID-19 or other diseases. – Limitations on each of the reviewed studies. 5. Methodology (10 Marks) – Description of predictive analytics process used to carry out the study. Draw a well labelled diagram to illustrate the process and cite the source of the process – screen shots of python code used to implement various steps of the process and respective outputs. 6. Results (10 Marks) -Screen shots and interpretations of visualized model. -Description of evaluation results obtained after testing the proposed model 7. Conclusion and Recommendations (5 Marks) – Opinion derived from the results References (2 Marks)

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYTICS MDA 5403: CYBER SECURITY AND COMPUTER FORENSICS DATE: MAY, 2020 TIME: 6 HOURS INSTRUCTIONS: Answer ALL Questions SECTION B QUESTION TWO (15 MARKS) a) Discuss the strength of Cryptosystem on basis of different parameters QUESTION TWO (15 MARKS) Irene works for a pharmaceutical company. One day, she arrives in her office and realizes that important files have been deleted from her workstation. Her workstation is a desktop computer running Windows 10, 500GB hard drive, connected to the Internet. She immediately called the forensic team to investigate the case. After receiving proper authorization, the team arrives and collects both a memory snapshot of the computer and a bit-stream image of its hard disk. Write three hypotheses for what may have happened, and explain how to proceed in order to falsify each hypothesis based on the collected data. Be specific on the kind of evidence to be looking for.

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYICS/MASTER OF SCIENCE IN INFORMATION SYSTEMS MANAGEMENT MDA 5304/MISM 5402: DATA MINING AND WAREHOUSING DATE: MAY 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take-Home Examination (THE) QUESTION ONE Every organization has a great deal of data and more data is being collected every day. In addition to the already large data-sets that exist today, many organizations are looking for ways to construct a classification model that can be used classify future objects and develop a better understanding of the classes of the objects in the data base. The aim of classification techniques is to generate more accurate classification results. However, existing classification techniques gives poor classification accuracy when compared to others. Therefore, there is need for comparing different classifiers and using the most accurate classifier. Requirements 1. Download data about Kenya from open online sources and use python libraries to carry out data preprocessing (5 Marks) 2. Use appropriate data mining tools such as Python libraries to apply any two different classification techniques and develop classification models (5 Marks) 3. Use python libraries to evaluate the accuracy of the two developed models to determine which model is more accurate given the same data. (5 Marks) 4. Write a research paper to communicate which among the studied techniques provides more accurate results. The paper should be structured as follows: i. Front Pages (3 Marks) – Title page, Glossary, acronyms, Abstract and table of content ii. Introduction (5 Marks) – Background of classification as a data mining task – Problem statement related to accuracy of classification – Objectives -Significance of the study iii. Literature Review (5 Marks) – Review of at least three studies that have used classification techniques to perform machine learning tasks for decision making support. – Limitations on each of the reviewed studies. iv. Methodology (5 Marks) – Description of the process used to develop classification models. Draw a well labelled diagram to illustrate the process and cite the source of the process – screen shots of python code used to implement various steps of the process and respective outputs. v. Results (10 Marks) – Screen shots of the two developed and visualized models. – Description of evaluation results obtained after testing both models with test data. vi. Conclusion and Recommendations (5 Marks) References (2 Marks)

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYTICS MDA 5302: HUMAN PERCEPTION & INFORMATION VISUALIZATION ORDINARY EXAMINATIONS DATE: MAY, 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take-Home Examination (THE) QUESTION 1 (15 MARKS) SGR trains are known to be not very punctual in its operations. You have been hired as an information visualization expert to build a system that can highlight whether there are trends and patterns or certain hidden insight that if known may help them improve their operations. The data at their disposal has; • For every day the departure and arrival times of all trains in all stations along the NairobiMombasa route. • All complaints from passengers over time The task is to find an appropriate way to visualise these data to enable them get an understanding of what the passengers consider as important. They also want to visualise these views as they change in the course of a delay. Required; • By reviewing a variety of visualisations including: Line plot, river pixel, matrix, Node-link, clouds, galaxies, maps. Text, glyph, icon etc, decide on which is the most appropriate techniques to capture the data at SGR’s disposal. Explain your answer and also give a sketch of the technique chosen. QUESTION 2 (15 MARKS) There are a number of institutions that are mapping the COVID-19 virus. Some good examples can be found at: • Johns Hopkins Data visualiser at; https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b 48e9ecf6 • Dashboard of the COVID-19 Virus Outbreak in Singapore at; https://co.vid19.sg/singapore/clusters • Tableaus COVID-19 data hub at; https://www.tableau.com/covid-19-coronavirus-data-resources Required; a) Identify 5 Information Visualization representations that best depict information around COVID-19 that you deem useful to the general public. Explain your choices and share the screenshots. b) Identify 5 Information Visualization representations that best depict information around COVID-19 that you deem useful to health workers. Explain your choices and share the screenshots. c) Critically analyse your choices above. Explain their shortcomings in view of their intended audiences and suggest ways that they can be improved. QUESTION 3 (20 MARKS) For a long time, graphs have been studied in mathematics and information technology and are naturally suited to representing entities where there is a network organization to represent. Graphs are a very efficient form of representation for network data, but unfortunately they have the disadvantage of not being very scalable: By increasing the number of nodes, the graph becomes too complex and not very readable. Required; Write a brief technical paper that reviews some of the ongoing research into the problem of complex graphs especially in relation to increasing the number of nodes representable in a graph, or to improving their legibility. Hint: The paper has capture the very recent research in graph visualization. Include in your submission a full list of references. Your paper has to adhere to the APA style. (paper should not be more than 3 pages, A4, font size 12 and 1.5 spacing).

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYTICS MDA 5301: LOGIC, SENSE MAKING&BUSINESS INTELLIGENCE ORDINARY EXAMINATIONS DATE: MAY, 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take-Home Examination (THE) QUESTION ONE (50 MARKS) In broad terms, business intelligence systems are used to maintain, optimize and streamline current operations. The term refers to technologies, applications and practices for the collection, integration, analysis and presentation of business information. The purpose of business intelligence is to support data-driven business decision making. Business intelligence is sometimes used interchangeably with briefing books, report and query tools, and executive information systems. BI improves and maintains operational efficiency and helps companies increase organizational productivity. Business intelligence software offers many benefits, including powerful reporting and data analytics capabilities. Using BI’s rich data visualization mechanisms like real-time dashboards, managers can generate intuitive, readable reports that contain relevant, actionable data. So BI offers reporting and analytics — isn’t that just two words for the same thing? Many people both in and outside the software industry incorrectly use reporting and analytics interchangeably, which is one cause for the confusion behind the BA/BI conflation. Reporting is “the process of organizing data into informational summaries in order to monitor how different areas of a business are performing.” It gathers data and delivers it in a digestible format. Analytics is “the process of exploring data and reports in order to extract meaningful insights, which can be used to better understand and improve business performance.” This function takes the “what” of the data given by reporting and draws conclusions and insights, offering users a “why” and “how.” Basically, reporting functions present data, and analytics features interpret data. Both are crucial features and will typically be offered by both BA and BI solutions. Additionally, business intelligence tools can analyze financial and operational statistics, identify weak areas and provide ways to address these issues. The trends found through data analysis help companies make better-informed, data-driven decisions. Other common BI features include data visualizations, decision services, integrations and online analytical processing (OLAP). Data visualizations serve a purpose similar to reporting. Both features function as a tool for the organization and presentation of data. Visualizations amplify reporting functions by offering data representations in an easy-to-interpret medium. Decision services narrow the focus of business intelligence to financial reporting, with many systems offering built-in compliance measures and fraud detection. Integration capabilities ensure a business intelligence system can work seamlessly with currently-in-place tools. Furthermore, integration features help pull data from multiple sources, from in-house databases to more complex Big Data centers. Many BI tools employ online analytical processing (OLAP) to perform sophisticated, multi-dimensional, drill-down analysis. In addition, BI offers a goal management function. Managers are able to program data based on goals, which may include sales goals, productivity measures or financial objectives, on a daily basis. BI features contribute to the goal of providing an awareness of current business practices. Popular business intelligence solutions include: QlikView, SAP Business Objects, Microsoft Power BI, IBM Cognos and Microstrategy. When considering the virtues of business intelligence software and the ways it differs from business analytics, it is important to acknowledge the function of BI as an evaluator of the past and present. It is used to make improvements right now. Business intelligence systems examine data on performance, finances, media reach and more, and report the information in a format that can be interpreted in a useful way. With the insights provided by business intelligence software, organizations can use their data to improve current processes. REQUIRED; 1. Review the literature to identify and understand the state of the art business intelligence techniques 2. Suggest a novel technique that you feel has never been applied in BI 3. Using a case (business, natural phenomena, governments etc) of your own choice to give suggestions of how your chosen technique can be operationalized. 4. Write a scholarly report Note: Plagiarism will attract 0 mark for the entire report. (50 Marks)

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYTICS MDA 5204: CURRENT ADVANCES IN DATABASES SECTION 2: OPEN-BOOK EXAMINATION DATE: MAY, 2020 TIME: 6 HOURS INSTRUCTIONS: Answer ALL Questions QUESTION ONE [15 MARKS] a) Explain the following concepts and offer a practical example for each: (3 Marks) i) Image query by keywords ii) Image query by example iii) Snapshot future query b) Discuss in detail any TWO multimedia database architectures. (2 Marks) c) A spatial database is a database that is optimized to store and query data related to objects in space. Illustrate how these objects are modeled. (4 Marks) d) Discuss the requirements for spatial querying. (6 Marks) QUESTION TWO [15 MARKS] Write short notes on the distributed query processing system paying attention to the following details: (a) How it compares with the parallel database structure (b) Catalog management in distributed databases. (c) Potential advantages and challenges of distributed databases. (15 Marks)

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYICS/MASTER OF SCIENCE IN INFORMATION SYSTEMS MANAGEMENT MDA 5203/MISM 5203: DECISION SUPPORT SYSTEMS DATE: MAY, 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take-Home Examination (THE) QUESTION ONE (50 MARKS) DSS is a computerized-based information system that organizes, collects, and analyzes business data that can be used in decision-making activities for the management, operations, and planning in an organization or business. The typical types of information that is gathered by a decision support system may include sales figures and projected revenue, inventory data that has been organized into relational databases for analysis, and comparative sales figures between specific, selected time periods. A good DSS helps decision-makers with compiling various types of data gathered from several different sources, including documents, raw data, management, business models and personal knowledge from employees. DSS applications can be used in a vast array of diverse fields, such as credit loan verification, medical diagnosis, business management, evaluating bids on engineering projects, agricultural production and railroad evaluation. DSS operates on several levels and there are many examples of common day-to-day use for decision support systems. For instance, GPS is used to determine the best and quickest route between two points. This task is completed by comparing and analyzing the option for multiple possibilities. GPS systems may also include features such as traffic avoidance, which monitors the traffic conditions between the two points, allowing you to avoid traffic congestion. One of the easiest ways to understand how DSS works is to consider your computer use; every time you log on and use a search engine, you’ve used a DSS to organize a massive amount of information and transform it into images, videos, and text files in order to choose the information that best suits your search. There are many ways DSS are used. Farmers use tools for crop-planning to help determine the best planting time, when to fertilize and when harvest. When DSS is used in medicine it is known as clinical DSS. The functions of clinical DDS may be used to manage details and complex information for a wide range of things, such as maintaining research information about chemotherapy protocols, preventative care, tracking orders and follow-up care. The system is often used for cost control, avoiding duplicate tests and monitoring medication orders. DSS is also used with medical diagnosis software, which provides medical personnel with the ability to diagnose illnesses. Some states have used DSS to provide information about potential hazards, such as floods. The system includes real-time weather conditions and may include information (current and historical) about floodplain boundaries and county flood data. Real estate companies often use DSS for information about properties, including current data such as neighborhood comparison prices, acreage and future planning. Universities and colleges rely on DSS to know how many students are currently enrolled, which allows them to predict how many additional students are needed in particular courses or overall population to ensure there are enough students enrolled to meet the university costs. REQUIRED: 1. Review the literature to understand contemporary technologies used in Decision Support Systems 2. Identify ways in which these technologies can be implemented in decision support systems to assist decision and policy makers in addressing epidemic issues such as for Corona virus. Suggest ways in which the following can be facilitated. a. Early Warning b. Diagnosis c. Prognosis d. Contact Tracing e. Social Distancing f. Logistics 3. Write a scholarly report Note: Plagiarism will attract 0 mark for the entire report. (50 MARKS)

UNIVERSITY EXAMINATIONS: 2019/2020 EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN DATA ANALYICS MDA 5202: MACHINE LEARNING DATE: MAY 2020 TIME: 14 DAYS INSTRUCTIONS: Answer ALL Questions Take-Home Examination QUESTION ONE In his 1982 book Megatrends, John Naisbitt wrote “We are drowning in information but starved for knowledge.” While written over 30 years ago, that line is as very true today. Every organization has a great deal of data and more data is being collected every day such as COVID-19 data. However, data is useless unless you can convert it to information and ultimately into knowledge. Machine learning techniques such as deep learning techniques are viewed as suitable tools for creating models that can provide knowledge. Requirements – Write a research paper that proposes a deep learning model for predicting a certain phenomenon in an organization, county or in Kenya. – Submit a Zip file that consists downloaded data, Research paper and a document with screen shots of python code and output – The paper should be structured as follows: 1. Front Pages (3 Marks) – Title page, Glossary, acronyms, Abstract and table of content 3. Introduction (10 Marks) – Background of phenomenon and deep learning techniques – Problem statement – Objectives -Significance of the study 4. Literature Review (10 Marks) – Review of at least three studies that have used deep learning algorithms to perform machine learning tasks for decision making support. – Limitations on each of the reviewed studies. 5. Methodology (10 Marks) – Description of the process used to develop deep learning model. Draw a well labelled diagram to illustrate the process and cite the source of the process – screen shots of python code used to implement various steps of the process and respective outputs. 6. Results (10 Marks) – Screen shots and interpretations of the visualized model. – Description of evaluation results obtained after testing the proposed model 7. Conclusion and Recommendations (5 Marks)

UNIVERSITY EXAMINATIONS: 2018/2019 EXAMINATION FOR THE DEGREE OF MASTERS OF SCIENCE IN DATA COMMUNICATIONS MDC6101 COMPUTER NETWORKS ORDINARY EXAMINATIONS DATE: AUGUST, 2019 TIME: 2 HOURS INSTRUCTIONS: Answer Question One & ANY OTHER TWO questions. QUESTION ONE (20 MARKS) (a) A variety of devices are used in networking and internetworking. Give any TWO clear differences in each of the following pairs. (6 Marks) (b) Use simple illustrations to compare and contrast the circuit switched and packet switched networks. (4 Marks) (c) Briefly explain how the Domain Name Service (DNS) is implemented and how DNS queries are resolved in the DNS system. (5 Marks) (d) Explain how FDDI network works. (5 Marks) QUESTION TWO (15 MARKS) (a) Use a diagram to describe the OSI seven-layer model by indicating a specific function of each layer. (7 Marks) (b) Differentiate between Distance Vector Routing Protocol and Link State Routing Protocol. (8 Marks) QUESTION THREE (15 MARKS) (a) Contrast the OSI model with the TCP/IP reference model using a diagram show the correspondence between relevant protocol layers in the two models. (3 Marks) (b) Discuss the relative merits of each of these models in the context of modern computer networking. (5 Marks) (c) A company is granted a site address 201.70.64.0. The company needs six subnets. Design the subnets. (7 Marks) QUESTION FOUR (15 MARKS) (a) Compare and contrast Client-server and peer-to-peer network, and suggest suitable uses of each. (5 Marks) (b) Discuss the issues and solutions related to the interworking of IPv6 and IPv4. (6 Marks) (c) Explain how ISDN works. (4 Marks)

UNIVERSITY EXAMINATIONS: 2018/2019 EXAMINATION FOR THE DEGREES OF MASTER OF SCIENCE IN DATA ANALYTICS MDA 5404: DATA ANALYTICS AND KNOWLEDGE ENGINEERING ORDINARY EXAMINATIONS DATE: AUGUST, 2019 TIME: 2 HOURS INSTRUCTIONS: Answer Question One & ANY OTHER TWO questions. QUESTION ONE (a) Briefly describe three limitations of descriptive analytics and explain how each of them can be addressed (3 Marks) (b) Discuss limitations of the following descriptive analytics measures and explain which other measures can be used to address the limitations (i) Mean (2 Marks) (ii) Covariance (2 Marks (c) Briefly explain how a combination of mode, median and mean can be used to determine whether data is skewed or symmetric (2 Marks) (d) Discuss the purpose of using Box plot in data analytics (2 Marks) (e) Briefly interpret the following data analytics visualization output. (3 Marks) (d) The following Table shows a list of hours studied and Marks received by 4 students Study hours Marks Use the above data set to compute measures for both study hours and Marks. Interpret results for each case (ii) Standard deviation (2 Marks) (iii) Covariance (2 Marks) (iv) Correlation (2 Marks) QUESTION TWO (a) Briefly discuss the relationship between ‘Data analytics’ and ‘Knowledge engineering’ (2 Marks) (b) Discuss three main goals of data analytics and their importance in business enterprises (3 Marks) (c) Describe the difference between descriptive and diagnostic analytics. Use a practical example to illustrate your answer (2 Marks) (d) Discuss the steps followed to carry out factor analysis including techniques for each step (5 Marks) (e) Consider the following knowledgebase of facts furniture (sink, kitchen,1). furniture (chair,lounge,4). furniture (bed,bedroom,1). furniture (cooker,kitchen,1). furniture (chair,kitchen,4). furniture (sofa,lounge,1). (i) Write a query that can be used to find the number of each item there are in the lounge (1 Mark) (ii) Write a query that can be used to list all the rooms without showing the furniture or the numbers (1 Mark) (iii) Write a query that can be used to find the number of chairs in each room (1 Mark) QUESTION THREE (a) Briefly describe the meaning of the following concepts as used in data analytics and knowledge engineering: (i) Eigen values (1 Mark) (ii) Normalization (1 Mark) (iii) Principal component analysis (1 Mark) (b) State and explain five knowledge engineering activities (5 Marks) (c) Discuss four components of a knowledge based system (4 Marks) (d) Construct Semantic Network of the following scenario (3 Marks) cats, bears and whales are mammals. Bears and cats have fur while whales and fish lives in water. Both mammals and fish are animal. QUESTION FOUR (a) Describe the difference between predictive and prescriptive analytics (1 Mark) (b) Describe predictive Analytics Process Cycle. (5 Marks) (c) Consider the following knowledge A lorry that has part a trailer, 18 wheels and has a large weight capacity. It is driven by a driver and its speed is 100kph. (i) Draw a frame that represents the above knowledge. (2 Marks) (ii) Use predicate logic to represent the above knowledge (2 Marks) (d) Consider the following data set Name Give Birth Can Fly Live in Water Have Legs Class Human Yes No no yes non-mammals Python No No no no non-mammals Salmon No No yes no non-mammals Whale Yes No yes no Mammals Frog No No yes yes Mammals Komodo No No no yes non-mammals Bat Yes Yes no yes Mammals Pigeon No Yes no yes non-mammals Cat Yes No no yes non-mammals leopard shark Yes No yes no non-mammals 4 Use the above data set to answer the following questions (i) identify independent and dependent attributes (1 Mark) (ii) Given that the split point =3,write sample python code to split the data set into test and training data set, (2 Marks) (iii)Write sample python code to split the data into independent and dependent attributes (2 Marks)