ISSS608 2017-18 T3 Assign Wang Runyu Data Visualization

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Brambling20male-zzzzzzzz.jpg VAST Mini Challenge 1: "Cheep" Shots?

Background

Data Preparation

Data Visualization

Conclusions

 


Patterns of all of the bird species

By

By quarter

Q2

Visual Analytical Approach

Remove Highly Correlated Features

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

Corr plot q2 visual method.png

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'.

Trellis Plot for Variable Density
Density plot q2 visual method.png

Machine Learning Approach

Random Forest

Decision Tree

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