JEMLAhttp://mloss.orgUpdates and additions to JEMLAenWed, 04 Feb 2015 11:37:00 -0000JEMLA 1.0<html><p>JEMLA is a Java package for calculating Entropy which is essential in several Machine Learning Applications. 6 algorithms for handling missing attributes are implemented in JEMLA. These 6 methods are: 1: Ignore missing values. 2: For categorical features, replace missing values with most common value; for numerical features, replace missing values with mean value. 3: In each given class or concept, perform method method 2 individually. 4: Find the used values of the feature for each given class and sort them based on the rate of their uses. Missing values would be replaced with different values and not most common values. Therefore the rate of a value accounts for the fraction of missing values which replaced by that value. 5: Perform like method 3 except that for numerical features, replace missing values with mid value. 6: Perform the “closest fit” algorithm. “Closest fit” is a preprocessing algorithm in which for each instance in the data set, finds the instance which has minimum Euclidean distance with that instance. Then replaces missing values based on matching value in the other instance. </p></html>NargesSadat BathaeianSun, 04 Jan 2015 08:34:49 -0000 learningmissing datajavaentropy<b>Comment by NargesSadat Bathaeian on 2015-01-04 08:36</b><p>Any documentation?</p> NargesSadat BathaeianSun, 04 Jan 2015 08:36:09 -0000<b>Comment by NargesSadat Bathaeian on 2015-02-04 11:37</b><p>Today I put a simple user guide for JEMLA. Please download it from</p> NargesSadat BathaeianWed, 04 Feb 2015 11:37:00 -0000