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利用Weka进行高级数据挖掘 | MOOC中国 - 慕课改变你,你改变世界


Advanced Data Mining with Weka

Learn how to use popular packages that extend Weka’s functionality and areas of application. Use them to mine your own data!

1100 次查看
  • 完成时间大约为 5
  • 初级
  • 英语


Discuss the use of lagged variables in time series forecasting

Explore the use of overlay data in time series forecasting

Identify several different applications of data mining with Weka

Compare incremental and non-incremental implementations of classifiers

Evaluate the performance of classifiers under conditions of concept drift

Classify tweets using various techniques

Calculate optimal parameter values for non-linear support vector machines

Demonstrate the use of R classifiers in Weka

Develop R commands and R scripts from Weka

Explain how distributed Weka runs Weka on a cluster of machines

Experiment with distributed implementations of Weka classifiers and clusterers

Explain how “map” and “reduce” tasks are used to distribute Weka

Design Python and Groovy scripts for Weka operations

Apply Python libraries to produce sophisticated visualizations of Weka output

Describe how Weka can be invoked from within a Python environment


This course will bring you to the wizard level of skill in data mining, following on from Data Mining with Weka and More Data Mining with Weka, by showing how to use popular packages that extend Weka’s functionality. You’ll learn about forecasting time series and mining data streams. You’ll connect up the popular R statistical package and learn how to use its extensive visualisation and preprocessing functions from Weka. You’ll script Weka in Python – all from within the friendly Weka interface. And you’ll learn how to distribute data mining jobs over several computers using Apache SPARK.


Time series analysis

Data stream mining

Incremental classifiers

Evolving data streams

Support vector machines

Accessing data mining in R

Distributed data mining

Map-reduce framework

Scripting data mining in Python and Groovy

Applications: Soil analysis, Sentiment analysis, Bioinformatics, MRI neuroimaging, Image classification


This course is aimed at anyone who deals in data. You should have completed Data Mining with Weka and More Data Mining with Weka – or be an experienced Weka user. Although the course includes some scripting with Python, you need no prior knowledge of the language. You will have to install and configure some software components; we provide full instructions.

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