Difference between revisions of "ISSS608 2017-18 T3 Assign Wang Runyu Data Visualization"
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===Machine Learning Approach=== | ===Machine Learning Approach=== | ||
− | + | ====Random Forest==== | |
====Decision Tree==== | ====Decision Tree==== |
Revision as of 11:10, 7 July 2018
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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 is 0.6.