2 publications

• Published Subscription 17 May 2018

  Data Mining Methods for Large Data

  By P. Arumugam, P. Jose

  Abstract: High dimensional data classification becomes a challenging task because data are large, complex to handle, heterogeneous and hierarchical. In order to reduce the data set without affecting the classifier accuracy, the feature selection plays a vital role in large datasets and which increases the efficiency of classification to choose the important features for high dimensional classification, when those features are irrelevant or correlated. Therefore feature selection is considered to be …

  Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 30s–35s Read article →

• Published Subscription 21 Mar 2018

  Data Mining Methods for Large Data

  By P. Jose, P. Arumugam

  Abstract: AbstractHigh dimensional data order ends up plainly difficult assignment since information are substantial, complex to deal with, heterogeneous and progressive. Keeping in mind the end goal to lessen the informational index without influencing the classifier precision. The element determination assumes a fundamental part in huge datasets and which expands the proficiency of arrangement to pick the vital highlights for high dimensional grouping, when those highlights are superfluous or corresponded. Along …

  Published in Recent Trends in Programming languages · Vol. 4, Issue 3, 2017 · pp. 1–6 Read article →