ISSS608 2017-18 T3 Assign Wang Runyu Data Visualization
Revision as of 11:36, 7 July 2018 by Runyu.wang.2017 (talk | contribs)
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Contents
Q1
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Q2
Visual Analytical Approach
As the text format outcome from seewave package(analyzeFolder function) contains 69 features, it is not practical for us to analyze all the features visually. In the first step, I use findCorrelation() function to eliminate highly correlated features. I set the pair-wise absolute correlation cut off to 0.6.
Correlation Plot
remove features based on corr plot observations
Corrplot, select variables, we not only consider to check the variables nearby, but all the variables For example, group of 'specSlape_sd', 'harmonics_median', 'peakFreq_median', I choose 'peakFreq_median'.