Question

Which of the following technique is well known to utilize class labels in feature selection for classification?
1)LDA
2)PCA (by dimensionality reduction)
3)both (a) and (b)
4)None of these

Answer 1

Answer:

Explanation:

Linear Discriminant Analysis (LDA) is most commonly used as dimensionality reduction technique in the pre-processing step for pattern-classification and machine learning applications. The goal is to project a dataset onto a lower-dimensional space with good class-separability in order avoid overfitting (“curse of dimensionality”) and also reduce computational costs.

Ronald A. Fisher formulated the Linear Discriminant in 1936 (The Use of Multiple Measurements in Taxonomic Problems), and it also has some practical uses as classifier. The original Linear discriminant was described for a 2-class problem, and it was then later generalized as “multi-class Linear Discriminant Analysis” or “Multiple Discriminant Analysis” by C. R. Rao in 1948 (The utilization of multiple measurements in problems of biological classification)