1 / 2

Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar

Objectives Data Mining Course. Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar. Using R for Data Analysis and Data Mining. Apply Data Mining to Real World Datasets. Exploratory Data Analysis and Preprocessing.

meda
Download Presentation

Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Objectives Data Mining Course Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar Using R for Data Analysis and Data Mining Apply Data Mining to Real World Datasets Exploratory Data Analysis and Preprocessing Goals and Objectives of Data Mining Making Sense of Data Implementing Data Mining Algorithms Classification Techniques Association Analysis Learn How to Interpret Data Mining Results Clustering Algorithms

  2. Top 10 Data Mining Algorithms C4.5 SVM K-means APRIORI EM PageRank AdaBoost kNN Naïve Bayes CART

More Related