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directlabels

Direct labels for multicolor plots in lattice or ggplot2

house-recommendation

pca-analysis

Principal components analysis is a useful tool in understanding the covariance structure of the data. This is accomplished by computing the linear combinations obtained by rotating the original axes which represent the direction of maximum variability and provide a parsimonious description of the covariance structure.There is no universal objective way to determine the number of principal components, typicallyit is subjected aided by one of the following: 1. the amount of total sample variance explained 2. relative sizes of eigen values 3. subject-matter interpretations 4. point of bend in the scree plot

tableau-visualization

traffic_congestion_detection

Detection of traffic congestion

us-accidents-analysis