10 pages
You have been asked by management (manufacturing, healthcare, retail, financial, and etc.,) to create a research report using a data mining tool, data analytic, BI tool. It is your responsibility to search, download, and produce outputs using one of the tools. You will need to focus your results on the data set you select.
Ensure to address at least one topic covered in Chapters 1-9 with the outputs. The paper should include the following as Header sections. You can find some related topics if you want. Then write the term paper.
Example of topics:
1. Using data mining techniques for learning systems.
2. How to Improve Health Care System using data mining techniques
3. Design and develop Network/Information Security using data mining techniques
4. How efficiently extract knowledge from big data using data mining techniques
5. Using data mining techniques to improve the financial/stock information systems
Types of Data Analytics Tools( Can use any of them):
https://www.octoparse.com/blog/top-30-big-data-tools-for-data-analysis/
Excel with Solver, but has limitations
R Studio
Tableau Public has a free trial
Microsoft Power BI
Search for others with trial options
Examples of Dataset:
http://www.rdatamining.com/
https://www.forbes.com/sites/bernardmarr/2016/02/12/big-data-35-brilliant-and-free-data-sources-for-2016/#4b3e96f1b54d
Example: Project Construction Format:
You should follow the following content format:
Title: Topic
Name: Logan Lee
ID: 123-45-567
Introduction
Background [Discuss tool, benefits, or limitations]
Review of the Data [What are you reviewing?]
Exploring the Data with the tool
Classifications Basic Concepts and Decision Trees
Other Alternative Techniques
Summary of Results
References
(Ensure to use the Author, APA citations with any outside content).
Assignment Instructions:
1. No ZIP file
2. The submitted assignment must be typed by ONE Single MS Word/PDF file.
3. At least 10 pages (not including heading and content list pages) and 5 references.
4. Use 12-font size and 1.5 lines space
5. No more than 4 figures and 3 tables
6. Follow APA style and content format: UC follows the APA (American Psychological Association) for writing style in all its courses which require a Paper or Essay.
http://www.apastyle.org/
Grading Rubrics:
This assignment is an individual work. Please do NOT co-working with colleagues to violate the academic integrity. Grading for this assignment will be based on answer of completed the above requirements, quality, logic/organization of the paper, and language and writing skills. Please see as follows:
Comprehension of Assignment (Addressed the question completely and thoroughly. Provided additional supporting evidence, demonstrating a full comprehension of subject matter): 20/20 points
Application of Course Knowledge and Content (Thorough technical application of course knowledge and content in a complete and concise manner): 20/20 points
Organization of Ideas (Original ideas are effectively developed and presented in a logical, sequential order throughout the entire assignment. Includes adequate and appropriate supporting evidence): 20/20 points
Writing Skills (Mechanics (spelling, grammar, and punctuation) are flawless, including proficient demonstration of citations and formatting throughout the entire assignment): 20/20 points
Research Skills (Accurate and applicable use of resources relevant to the subject matter that enhance the overall assignment): 20/20 points
CLASSIFICATION IN SUPERVISED LEARNING
Name
Institutional affiliation
Date
SUPERVISED LEARNING
Supervised learning proposes an alternative to artificial intelligence ( AI), in which input information and anticipated resulting data are labeled for the project. The Autonomous robot is told what to search for. The model is educated so it can understand the fundamental trends and patterns, allowing it to deliver excellent results when faced with information never seen before.
There are two methodologies of Supervised Learning: Regression as well as classification. Classification distinguishes information, Regression suits information. (Mrukwa 2018 Classification is a supervised method of learning. This defines the subclass to which data sets belong whenever the output has unique and specific values, which is better utilized. This also estimates one class for independent variables.
Supervised classification is among the activities that so-called Intelligent Systems more commonly perform. (Katsiantis et al. 2006) Classification is a method by which a given collection of data is categorized from multiple sources and it can be performed on both information. The process starts by forecasting the form of given data points. The groups are known as , signs, or sections. (Waseem 2019)
Classification therefore estimates propositional class labels or categorizes information based on training collection and element identification attributes, and utilizes it in the discovery of new data. There are several frameworks for the grouping. Logistic regression, decision tree, nave bayes, gradient-boosted tree, multilayer perceptron, version-vs-rest, and random forest are among the classification algorithm. Some concrete examples of classification issues include: acknowledgement of speech, acknowledgement of writing, detection of bio metrics, processing of documents etc.
REFERENCES
Kotsiantis, Sotiris & Zaharakis, I. & Pintelas, P.. (2006). Machine learning: A review of classification and combining techniques. Artificial Intelligence Review. 26. 159-190. 10.1007/s10462-007-9052-3.
Mrukwa, E. (2018, October 8). Types of machine learning algorithms: Supervised and unsupervised learning. https://www.netguru.com/blog/supervised-machine-learning
Waseem, M. (2019, December 4). Classification in machine learning | Classification algorithms |Edureka. https://www.edureka.co/blog/classification-in-machine-learning/
