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DWDM lab exp2

 

  1. Explore machine learning tool“WEKA”//2.a//Explore WEKA Data Mining/Machine Learning Toolkit. ANS:

WEKA(Waikato Environment for Knowledge Analysis) an open-source software provides tools for data preprocessing, implementation of several Machine Learning algorithms, and visualization tools so that we can develop machine learning techniques and apply them to real-world data mining problems.

Features of WEKA -

  1. Preprocessor – Most of the Data is Raw. Hence, Preprocessor is used to clean the noisy data.

  2. Classify – After preprocessing the data, we assign classes or categories to items.

  3. Cluster – In Clustering, a dataset is arranged in different groups/clusters based on some similarities.

  4. Associate – Association rules highlight all the associations and correlations between items of a dataset.

  5. Select Attributes – Every dataset contains a lot of attributes; only significantly valuable attributes are selected for building a good model.

  6. Visualize – In Visualization, different plot matrices and graphs are available to show the trends and errors identified by the model.




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