PCA for mixed data
I am performing analysis on a bunch of data of measurement readings. In the experiment, we have several factors which are of numerical and categorical. In order to find which of these are significant I plan to do a PCA and find the correlation of the PCA components with the individual factors. However, I am not sure of how one should encode the categorical variables to not (significantly) effect the result of the PCA as that would effect the variation capture result in the components. I have also checked MCA but to my understanding it is only applicable to categorical variables and I do not want to ignore the relationship between both types of variables which affect the measured values. Can anyone suggest how to go about this?
Thanks very much!
python pca analysis
asked Nov 21 '18 at 12:37
SyemanSyeman
62
add a comment |
I am performing analysis on a bunch of data of measurement readings. In the experiment, we have several factors which are of numerical and categorical. In order to find which of these are significant I plan to do a PCA and find the correlation of the PCA components with the individual factors. However, I am not sure of how one should encode the categorical variables to not (significantly) effect the result of the PCA as that would effect the variation capture result in the components. I have also checked MCA but to my understanding it is only applicable to categorical variables and I do not want to ignore the relationship between both types of variables which affect the measured values. Can anyone suggest how to go about this?
Thanks very much!
python pca analysis
asked Nov 21 '18 at 12:37
SyemanSyeman
62
add a comment |
I am performing analysis on a bunch of data of measurement readings. In the experiment, we have several factors which are of numerical and categorical. In order to find which of these are significant I plan to do a PCA and find the correlation of the PCA components with the individual factors. However, I am not sure of how one should encode the categorical variables to not (significantly) effect the result of the PCA as that would effect the variation capture result in the components. I have also checked MCA but to my understanding it is only applicable to categorical variables and I do not want to ignore the relationship between both types of variables which affect the measured values. Can anyone suggest how to go about this?
Thanks very much!
python pca analysis
asked Nov 21 '18 at 12:37
SyemanSyeman
62
I am performing analysis on a bunch of data of measurement readings. In the experiment, we have several factors which are of numerical and categorical. In order to find which of these are significant I plan to do a PCA and find the correlation of the PCA components with the individual factors. However, I am not sure of how one should encode the categorical variables to not (significantly) effect the result of the PCA as that would effect the variation capture result in the components. I have also checked MCA but to my understanding it is only applicable to categorical variables and I do not want to ignore the relationship between both types of variables which affect the measured values. Can anyone suggest how to go about this?
Thanks very much!
python pca analysis
python pca analysis
asked Nov 21 '18 at 12:37
SyemanSyeman
62
asked Nov 21 '18 at 12:37
SyemanSyeman
62
asked Nov 21 '18 at 12:37
SyemanSyeman
62
asked Nov 21 '18 at 12:37
SyemanSyeman
62
asked Nov 21 '18 at 12:37
SyemanSyeman
62
62
add a comment |
add a comment |
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