Engineering Homework Help

Assignment 3 provides foundational learning about predictive modeling in analytics, and we only focus on decision trees. A decision tree is one approach/algorithm providing predictive models to help in decision making. It is ONE of many types of supervised learning algorithms. Some common supervised models/algorithms are, again we are only covering Decision Trees.

• Nearest Neighbor
• Naive Bayes
• Decision Trees
• Linear Regression
• Support Vector Machines (SVM)
• Neural Networks

For assignment 3 you will need to have ONE target variables with different models, meaning each model would have different variables predicting the target variable.

Yelena covers extensively decision trees, rules, and sunburst in her IBM CA zoom session video. I am attaching the zoom session slides. See attached slide specifically focus on slide numbers 40-42. I highly recommend you watch the section in Yelena’s video about Decision Trees. Additionally, the information provided in Week 6 class content provides several resources about Decision Trees.

https://www.youtube.com/watch?v=93g9qk1D_hU

Additionally, Yelena new short videos cover Decision Trees and Sunburst driver analysis. Here is the playlist for all the videos:

https://www.youtube.com/playlist?list=PL2r2WGYKOnJWvwjzgazpro6MzdmvLZqBj

For example, Yelena has a short video about Sunbursts:

https://www.youtube.com/watch?v=67hHz_zAQ3M&list=PL2r2WGYKOnJWvwjzgazpro6MzdmvLZqBj