R studio dateset Assignment/SWOT
Unit 3 Assignment: Nearest Neighbors for Categorical Prediction
Outcomes addressed in this activity:
Integrate methods for assessing risks.
Prepare a rubric for classifying risk.
Report results of risk analysis.
IT528-3: Develop appropriate action plans that address risks.
There are many methods for categorical prediction using principal components. In this Assignment, you will practice one of these — linear discriminant analysis, in R Studio. You will classify risk through the rubric of a risk matrix and then build a model to assess the risk. Once you have built a model, you will report and explain the results.
Complete the following steps:
Much has been made of the deteriorating public infrastructure in the United States. Roads, bridges, sidewalks, etc. need repair all over the country. This Assignment will focus on bridges. Engineers with responsibility for bridges categorize them into one of four categories with respect to risk: Monitor, Schedule Assessment, Schedule Repair/Replacement, or Immediate Repair/Replacement. Monitor means that the bridge is in good condition and is not in danger of failing. Schedule Assessment means that the bridge is showing signs of risk and should be evaluated. Schedule Repair/Replacement means that the bridge has deterioration that presents risk to users. Immediate Repair/Replacement means that the bridge has deterioration that presents risk of failure. In a Word document, create a four-quadrant risk matrix rubric and label the quadrants High Risk/High Impact; High Risk/Low Impact; Low Risk/High Impact; Low Risk/Low Impact. Place each of the four bridge conditions into the quadrant that you believe is appropriate for that condition. You need not have something in each of the four quadrants – your task is to appropriately assess and classify risk based on bridge condition. For each of the four bridge conditions, within the quadrant you selected in the risk matrix, give an example of an issue that may arise if the risk condition is not addressed.
Download the Bridges.csv and the ConditionUnknown.csv files from Course Documents. Import both of these into R Studio with appropriate names. In your Word document, provide evidence that you have imported the data sets.
Build a linear discriminant analysis model using the Bridges.csv data. Document each step in your Word document.
You will need to load the MASS library.
Create the linear discriminant analysis model for the Bridge_Action variable. Use this syntax: BridgeModel <- lda(Bridge_Action~., data=Bridges) Note that you are creating a data object called BridgeModel, and the data that you are using to create your LDA model is called Bridges (you may have named your training data something other than Bridges when you imported Bridges.csv. Make predictions for the Condition Unknown bridges using the LDA model you created in step (b) above. Use this syntax: BridgePredict <- predict(BridgeModel, CondUnk) Note that you are creating a data object called BridgePredict that will apply the BridgeModel LDA object to a data object called CondUnk (you may have named your condition unknown data something other than CondUnk when you imported ConditionUnknown.csv). Put your LDA predictions into a data frame so that you can read and interpret them. Use this syntax: MyPredictions <- data.frame(BridgePredict$class, round(BridgePredict$posterior, digits=3)*100). Open the MyPredictions data frame and examine your prediction results. Answer the following in your Word document: How many bridges do you predict will be in each action category? What does the round function in step (d) above do to the posterior values in your predictions? What do the posterior values tell you about each prediction? (Hint: add them up). Give three ways that a city or county might use the predictions you have generated to manage their infrastructure plan? Give two risks that may arise from use of your predictions. Make sure that you cite at least five supporting sources beyond the textbook in support of your writing and explanations. Cite correctly in APA format. Assignment Requirements Prepare your Assignment submission in Microsoft Word following standard APA formatting guidelines: Double spaced, Times New Roman 12-point font, one inch margins on all sides. Include a title page, table of contents and references page. You do not need to write an abstract. Label all tables and figures. Cite sources appropriately both in the text of your writing (parenthetical citations) and on your references page (full APA citation format).