Machine Learning and AI: Advanced Decision Trees with SPSS
In a recent advanced course on decision trees I completed on LinkedIn Learning, I learned about the QUEST and C5.0 algorithms and their practical applications. The course covered how these algorithms handle various types of data, including nominal, ordinal, and continuous variables, as well as missing data. These insights are particularly relevant to my major in MIS, as they provide valuable techniques for data preprocessing, essential for tasks such as business intelligence and predictive analytics. I gained a better understanding of fundamental concepts like information gain and explored topics such as boosting and bagging, which are crucial for improving model performance in technological applications.