Machine learning techniques for Dimensionality Reduction and Comparative

 
   Lead Investigator:    Kashif Javed Lone
   Institution      :    University of Azad Jammu and Kashmir
   E-Mail           :    insaaftimber@gmail.com
   Proposal ID      :    842



   Proposal Description:
   The accuracy at which the decision support system predicts or classifies the      samples is of main concern in several domains especially in the field of          medical science. The major problem that raise is the curse of dimensionality      few samples but the thousand of features. This makes the problem very             complicated. so, taking in view the problem discussed above, we are going         1- To use machine learning dimensionality reduction (feature selection and        feature extraction) techniques on Alzheimer disease data (High Dimensional        data).                                                                            2- We also develop different models to classify Alzheimers patients.