Conclusion – Scatter Matrix
Scatter matrices are invaluable tools in engineering mathematics and data science, facilitating the exploration and analysis of complex datasets. They aid in identifying correlations, detecting outliers, and selecting features, ultimately enhancing the data modeling process.
Problem Solving on Scatter Matrix
A scatter matrix, also known as a pair plot, is a powerful visualization tool in data analysis. It provides a grid of scatter plots that display relationships between pairs of variables in a dataset, helping engineers and data scientists to identify patterns, correlations, and potential outliers.
Read More: Scatter Plot Matrix
We calculate Sw ( within the class scatter matrix ) and SB ( between the class scatter matrix ) for the available data points.
SW : To minimize variability within a class, inner class scatter.
SB : To increase between class variability, between class scatter.
scatter plot of the points
X1 = (y1, y2) ={ (2,2), (1,2), (1,2), (1,2), (2,2) } X2 = (y1,y2) ={ (9, 10), (6,8), (9,5), (8,7), (10,8) }
Within class scatter matrix:
[Tex]S_W = \sum_{i=1}^{c}S_i \\ S_i = \sum_{x\in D_i}^{c} (x-m_i)(x-m_i)^{T}[/Tex]
Si is the class specific covariance matrix. mi is the mean of individual class
Contact Us