| Author: | | Michael Furner |
| Category: | | Preprocessing |
| Date: | | 2018-08-18 |
| Depends: | | weka (>=3.7.1), EMImputation (>=1.0.1) |
| Description: | | Class that implements the DMI imputation algorithm for imputing missing values in a dataset. DMI splits the dataset into horizontal segments using a C4.5 (J48) decision tree in order to increase the correlation between attributes for EMI. EMI is performed to impute missing numerical attribute values and mean/mode (within a leaf) imputation is used to perform missing categorical attribute values. Uses Amri Napolitano's EMI implementation for Weka. |
| License: | | GPL 3.0 |
| Maintainer: | | Michael Furner <mfurner{[at]}csu.edu.au> |
| PackageURL: | | http://csusap.csu.edu.au/~zislam/code/DMI.zip |
| URL: | | http://csusap.csu.edu.au/~zislam/ |
| Version: | | 1.1 |