The Altair Community is migrating to a new platform to provide a better experience for you. The RapidMiner Community will merge with the Altair Community at the same time. In preparation for the migration, both communities are on read-only mode from July 15th - July 24th, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here.
Options

please help me I'm just beginner https://archive.ics.uci.edu/ml/datasets.php

learnhardlearnhard Member Posts: 3 Newbie

.

1. Conduct any data preparation that you need for your data set. This may include handling inconsistent data, dealing with missing values, or changing data types. Remember that in order to calculate means, each attribute in your data set will need to be numeric. If, for example, one of your attributes contains the values ‘yes’ and ‘no’, you may need to change these to be 1 and 0 respectively, in order for the k-Means operator to work. 

2.Connect a k-Means operator to your data set, configure your parameters (especially set your k to something meaningful for your question) and then run your model. 

3. Investigate your Centroid Table, Folder View, and the other evaluation tools. 

4. Report your findings for your clusters. Discuss what is interesting about them and describe what iterations of modeling you went through, such as experimentation with different parameter values, to generate the clusters. Explain how your findings are relevant to your original question

5.Experiment with the other k-Means operators in RapidMiner, such as Kernel or Fast. How are they different from your original model? Did the use of these operators change your clusters, and if so, how? 

Best Answer

Answers

Sign In or Register to comment.