This course on Advanced Data Mining with Weka aims to teach learners about advanced techniques in data mining using the Weka software. The course covers topics such as linear regression, time series forecasting, incremental classifiers, MOA package, LibSVM, LibLINEAR, R integration, distributed Weka with Apache Spark, and Python integration. By the end of the course, students will be able to apply these techniques to various real-world applications such as soil sample analysis, bioinformatics, neuroimaging data, and image classification. The course is designed for individuals interested in enhancing their data mining skills and knowledge using the Weka tool.
Overview
Syllabus
Advanced Data Mining with Weka: trailer.
Advanced Data Mining with Weka (1.1: Introduction).
Advanced Data Mining with Weka (1.2: Linear regression with lags).
Advanced Data Mining with Weka (1.3: timeseriesForecasting package).
Advanced Data Mining with Weka (1.4: Looking at forecasts).
Advanced Data Mining with Weka (1.5: Lag creation, and overlay data).
Advanced Data Mining with Weka (1.6: Application: Infrared data from soil samples).
Advanced Data Mining with Weka (2.1: Incremental classifiers in Weka).
Advanced Data Mining with Weka (2.2: Weka’s MOA package).
Advanced Data Mining with Weka (2.3: The MOA interface).
Advanced Data Mining with Weka (2.4: MOA classifiers and streams).
Advanced Data Mining with Weka (2.5: Classifying tweets).
Advanced Data Mining with Weka (2.6: Application to Bioinformatics – Signal peptide prediction).
Advanced Data Mining with Weka (3.1: LibSVM and LibLINEAR).
Advanced Data Mining with Weka (3.2: Setting up R with Weka).
Advanced Data Mining with Weka (3.3: Using R to plot data).
Advanced Data Mining with Weka (3.4: Using R to run a classifier).
Advanced Data Mining with Weka (3.5: Using R to preprocess data).
Advanced Data Mining with Weka (3.6: Application: Functional MRI Neuroimaging data).
Advanced Data Mining with Weka (4.1: What is distributed Weka?).
Advanced Data Mining with Weka (4.2: Installing with Apache Spark).
Advanced Data Mining with Weka (4.3: Using Naive Bayes and JRip).
Advanced Data Mining with Weka (4.4: Map tasks and Reduce tasks).
Advanced Data Mining with Weka (4.5: Miscellaneous capabilities).
Advanced Data Mining with Weka (4.6: Application: Image classification).
Advanced Data Mining with Weka (5.1: Invoking Python from Weka).
Advanced Data Mining with Weka (5.2: Building models).
Advanced Data Mining with Weka (5.3: Visualization).
Advanced Data Mining with Weka (5.4: Invoking Weka from Python).
Advanced Data Mining with Weka (5.5: A challenge, and some Groovy).
Advanced Data Mining with Weka (5.6: Course summary).
Taught by
WEKA MOOC
