Title :
A comparison of neural nets to statistical stubborn classification problems
Author :
Davies, Patricia ; Silverstein, Brian R.
Author_Institution :
Purdue Univ., West Lafayette, IN, USA
Abstract :
This paper addresses two types of problems which prove difficult for traditional classifiers: having very limited training data for at least one class, and having classes with a large amount of overlap. Issues discussed will include the (1) use of nearest neighbor methods and neural nets for classification of data which is completely inseparable by linear and quadratic classifiers, (2) dealing with training sets of unequal size from each class
Keywords :
learning (artificial intelligence); pattern classification; statistical analysis; data classification; limited training data; linear classifiers; nearest neighbor methods; neural nets; quadratic classifiers; statistical stubborn classification; unequal size training sets; Backpropagation; Density functional theory; Gaussian distribution; Nearest neighbor searches; Neural networks; Probability density function; Training data; Voting;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479732
