Implemented Dimensionality Reduction (PCA,LDA) and Clustering techniques (K-means)

DATASET: I have used two Datasets from UCI Library: 1.IRIS-Data 2.Arcene-Data 3.Breast-Cancer-Wisconsin-Data

Projection of the original data in PCA space (PC1 versus PC2; PC1 versus PC3 and PC2 versus PC3) and 1-dimensional LDA space

RESULTS: For K-means: 1. IRIS-Data: a) Internal Measures​: Parity:​0.866666666667 F­measure:​0.868622315348

		b) External Measures: 
			BetaCv:​0.309307295731 
			Nc:​0.862679327162
		
	2. Breast-Cancer-Wisconsin-Data
		a) Internal Measures: 
			Parity:​ 0.655221745351 
			F­measure: 0.637355865642 
		
		b) External Measures: 
			BetaCv:​ 0.264134236196 
			Nc:​ 0.690044336725