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I have data set of 100 variables(including output variable Y), I want to reduce the variables to 40 by PCA, and then predict variable Y using those 40 variables.

Problem 1: After getting principal components and choosing first 40 components, if I apply regression on it I get some function which fits the data. But how to predict some variable Y from the original data? To predict variable Y I have (100-1) variables at the input, and how do I know which 40 variables to choose out of my original 100-1 variables?

Problem 2: I do reversing of the PCA and get the data back from those 40 principal components. But the data are changed because I chose only first 40 components. Does applying regression to these data make any sense?

I use Matlab/Octave.

I have data set of 100 variables(including output variable Y), I want to reduce the variables to 40 by PCA, and then predict variable Y using those 40 variables.

Problem 1: After getting principal components and choosing first 40 components, if I apply regression on it I get some function which fits the data. But how to predict some variable Y from the original data? To predict variable Y I have (100-1) variables at the input, and how do I know which 40 variables to choose out of my original 100-1 variables?

Problem 2: I do reversing of the PCA and get the data back from those 40 principal components. But the data are changed because I chose only first 40 components. Does applying regression to these data make any sense?

I use Matlab/Octave.

I have data set of 100 variables(including output variable Y), I want to reduce the variables to 40 by PCA, and then predict variable Y using those 40 variables.

Problem 1: After getting principal components and choosing first 40 components, if I apply regression on it I get some function which fits the data. But how to predict some variable Y from the original data? To predict variable Y I have (100-1) variables at the input, and how do I know which 40 variables to choose out of my original 100-1 variables?

Problem 2: I do reversing of the PCA and get the data back from those 40 principal components. But the data are changed because I chose only first 40 components. Does applying regression to these data make any sense?

I use Matlab/Octave.

3 keyword spelling

I have data set of 100 variables(including output variable Y), I want to reduce the variables to 40 by PCA, and then predict variable Y using those 40 variables.

Problem 1: After getting principleprincipal components and choosing first 40 components, if I apply regression on it I get some function which fits the data. But how to predict some variable Y from the original data? To predict variable Y I have (100-1) variables at the input, and how do I know which 40 variables to choose out of my original 100-1 variables?

Problem 2: I do reversing of the PCA and get the data back from those 40 principleprincipal components. But the data are changed because I chose only first 40 components. Does applying regression to these data make any sense?

I use Matlab/Octave.

I have data set of 100 variables(including output variable Y), I want to reduce the variables to 40 by PCA, and then predict variable Y using those 40 variables.

Problem 1: After getting principle components and choosing first 40 components, if I apply regression on it I get some function which fits the data. But how to predict some variable Y from the original data? To predict variable Y I have (100-1) variables at the input, and how do I know which 40 variables to choose out of my original 100-1 variables?

Problem 2: I do reversing of the PCA and get the data back from those 40 principle components. But the data are changed because I chose only first 40 components. Does applying regression to these data make any sense?

I use Matlab/Octave.

I have data set of 100 variables(including output variable Y), I want to reduce the variables to 40 by PCA, and then predict variable Y using those 40 variables.

Problem 1: After getting principal components and choosing first 40 components, if I apply regression on it I get some function which fits the data. But how to predict some variable Y from the original data? To predict variable Y I have (100-1) variables at the input, and how do I know which 40 variables to choose out of my original 100-1 variables?

Problem 2: I do reversing of the PCA and get the data back from those 40 principal components. But the data are changed because I chose only first 40 components. Does applying regression to these data make any sense?

I use Matlab/Octave.

2 light editing

# How can oneto apply regression on PCAprincipal components to predict an output variable?

I have data set of 100 variables(including output variable Y)  , I want to reduce the variables to 40 by PCA  , and then predict variable Y using those 40 variables.

Problem 1 :Problem 1: After getting principle components , and choosing first 40 components  , if I apply regression on it I get some function , which fits the data. But Howhow to predict some variable Y now offrom the original data  ? because toTo predict variable Y I have (100-1) variables at the input  , and Howhow do I know which 40 variables to chosechoose out of my original 100-1 variables?

Problem 2 :Problem 2: I do reversing of the PCA and get the data back from those 40 principle components. But , the data isare changed because I choosechose only first 40 components. IsDoes applying regression in thisto these data make any sense  ?

Please tell me if I am able to deliver the question properlyuse Matlab/Octave.

# How can one apply regression on PCA components to predict output variable?

I have data set of 100 variables(including output variable Y)  , I want to reduce the variables to 40 by PCA  , and then predict variable Y using those 40 variables.

Problem 1 : After getting principle components , and choosing first 40 components  , if I apply regression on it I get some function , which fits the data. But How to predict some variable Y now of the original data  ? because to predict variable Y I have (100-1) variables at the input  , and How do I know which 40 variables to chose out of my original 100-1 variables?

Problem 2 : I do reversing of the PCA and get the data back from those 40 principle components. But , the data is changed because I choose only first 40 components. Is applying regression in this data make any sense  ?

Please tell me if I am able to deliver the question properly.