MINING Final Review Instructor: Yizhou Sun yzsun@cs.ucla.edu - PowerPoint PPT Presentation

CS145: INTRODUCTION TO DATA MINING Final Review Instructor: Yizhou Sun yzsun@cs.ucla.edu December 6, 2017

Learnt Algorithms Vector Data Set Data Sequence Data Text Data Classification Logistic Regression; Naïve Bayes for Text Decision Tree ; KNN; SVM ; NN K-means; hierarchical PLSA Clustering clustering; DBSCAN; Mixture Models Linear Regression Prediction GLM* Apriori; FP growth GSP; PrefixSpan Frequent Pattern Mining DTW Similarity Search 2

Final Exam • Time • 12/13, 11:30am-1:30pm • Location • Royce Hall 362 • Policy • Closed book exam • You can take two “reference sheets” of A4 size, i.e., one in addition to the midterm “reference sheet” • You can bring a si simple ple calculator 3

Content to Cover • All the content learn so far Vector Data Set Data Sequence Text Data • ~20% before midterm Data Logistic Naïve Bayes for Classification • ~80% after midterm Regression; Text Decision Tree ; KNN; SVM ; NN Clustering K-means; PLSA hierarchical clustering; DBSCAN; Mixture Models Prediction Linear Regression GLM* Apriori; FP GSP; PrefixSpan Frequent growth Pattern Mining DTW Similarity Search 4

Type of Questions • Similar to Midterm • True or false • Conceptual questions • Computation questions 5