Изменения
Добавил Джява пример
println(bits.bits.mkString(" "))
}
==Пример на языке Java==
Пример уменьшения размерности датасета с применением <code>weka.attributeSelection.PrincipalComponents</code><ref>[http://weka.sourceforge.net/doc.dev/weka/attributeSelection/PrincipalComponents.html/ Weka, PCA]</ref>
Maven зависимость:
<dependency>
<groupId>nz.ac.waikato.cms.weka</groupId>
<artifactId>weka-stable</artifactId>
<version>3.8.0</version>
</dependency>
'''import''' weka.attributeSelection.PrincipalComponents;
'''import''' weka.core.Instances;
'''import''' weka.filters.Filter;
'''import''' weka.filters.unsupervised.attribute.NumericToNominal;
'''import''' java.io.BufferedReader;
'''import''' java.io.FileReader;
// load dataset
'''var''' data = new Instances(new BufferedReader(new FileReader("data/bank-data.arff")));
'''var''' filter = new NumericToNominal();
filter.setInputFormat(data);
data = Filter.useFilter(data, filter);
// initialize the PCA-based selector
'''var''' pca = new PrincipalComponents();
// dimensionality reduction is achieved through selecting enough eigenvectors to account
// for some percantege of the variance in the original data
pca.setVarianceCovered(0.95);
pca.buildEvaluator(data);
// transform the dataset
data = pca.transformedData(data);
==См. также==
