Weka in Java for Feature Selection

program will perform the following, when given two command line arguments: [url removed, login to view] and K.

1. Study the use of at least two feature selection methods and two classification methods (all selected by you from those provided by Weka).

2. For each combination of feature selection method X and classification method Y, perform 2 fold cross validation. In each fold call Y to build a classifier on the feature set selected by X.

3. Your program will write the average accuracy and AUC of the classification result for each of the four combinations into a file called ClassificationResult.csv. The top five rows of the file will contain the header (accuracy and AUC) and one row for each combination.

4. The executable file should be called p2weka.

Taidot: Big Data, Java, Ohjelmistojen testaus

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About the Employer:
( 3 reviews ) MIAMISBURG, United States

Projektin tunnus: #13469456

Myönnetty käyttäjälle:

25 $ USD 1 päivässä
(25 arvostelua)