Discuss potential problems and improvements

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Reference no: EM133797068

Assignment: Data Analytics

The project should include the following items:

A. Find a business problem and define an analytical quesiton that can be tested and analyzed. Ideally, the analytical question should be predictive or diagnostic.

B. Find a dataset, which can be used to answer your question. The dataset should have at least 100 rows, one target variable, and at least 3 features for supervised learning. It should have at least 100 rows and at least 3 features for clustering analysis.

C. Determine the type of model based on the question (regression, classificaiton, clustering), and pick the best set of variables for your analysis.

D. Do the analysis and conclude.

In the written report and presentation, each group should include the following items:

A. Describe the research question, background information and the motivation of study.

B. Describe your dataset, including data source, data collection method, definition of columns, descriptive statistics.

C. Describe of the model(s), including the name of the model, why do you pick it, how do you want to use it (what is the target and what is the features). Get the instant assignment help.

D. Perform the data analysis, describe and discuss the results, including how you run the model, what results you get, what findings you get from the results.

a. You need to use at least one model learned from the class (including: K-means clustering, hierarchical clustering, linear regression, logistic regression, decision tree, SVM)

E. Do the model evaluation (evaluate the model to see whether it is good).

F. Discuss potential problems and improvements.

Reference no: EM133797068

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