<p>When using canonical correlation analysis (CCA), we can integrate the dataset and label information via transforming the class label matrix <em>Y</em> into the class indicator matrix <em>T</em>. Such as: $T = (YY^T)^½Y$ in [this article on LS CCA][1].</p>

<p>While for the numeric dataset and the binary dataset, the binary dataset can be viewed as the class label matrix and transformed into the class indicator matrix. After that, should I use the CCA? </p>

<p>Though without this transformation, [the CCA can be used][2], I'd like to know how to explian this kind of transformation once using it on the binary dataset (not label matrix). Thank you.</p>

CC BY-SA 3.0
2014-05-23T15:08:32.187Z
This might be better suited for [stats.se]
Suresh Venkat
CC BY-SA 3.0
2014-05-26T01:26:28.783Z
Well, I do, But nobody reply it. Consequently, I posted it here because I believe it's also a machine learning problem.
Zhilong Jia
<machine-learning><st.statistics>
What's the meaning of the class indicator matrix when transforming the class label matrix into it in canonical correlation analysis?
Zhilong Jia
# What's the meaning of the class indicator matrix when transforming the class label matrix into it in canonical correlation analysis?

(Asked by: username_0 on 2014-05-23)

When using canonical correlation analysis (CCA), we can integrate the dataset and label information via transforming the class label matrix *Y* into the class indicator matrix *T*. Such as: $T = (YY^T)^½Y$ in [this article on LS CCA][1].

While for the numeric dataset and the binary dataset, the binary dataset can be viewed as the class label matrix and transformed into the class indicator matrix. After that, should I use the CCA?

Though without this transformation, [the CCA can be used][2], I'd like to know how to explian this kind of transformation once using it on the binary dataset (not label matrix). Thank you.

**Tags:** machine-learning, st.statistics
> **Comments:**
> **username_1**: This might be better suited for [stats.se]  
> **username_0**: Well, I do, But nobody reply it. Consequently, I posted it here because I believe it's also a machine learning problem.  

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## 0 answers

