Knowing Feature Importance from Sparse Matrix
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I was working with a dataset which had a textual column as well as numerical columns, so I used tfidf for textual column and created a sparse matrix, similarly for the numerical features I created a sparse matrix using scipy.sparse.csr_matrix and combined them with the text sparse features.
Then I'm feeding the algorithm to a gradient boosting model and doing the rest of the training and prediction. However I want to know, is there any way I can plot the feature importance, of this sparse matrix and will be able to know the important feature column names?
machine-learning python nlp feature-selection
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
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add a comment |
$begingroup$
I was working with a dataset which had a textual column as well as numerical columns, so I used tfidf for textual column and created a sparse matrix, similarly for the numerical features I created a sparse matrix using scipy.sparse.csr_matrix and combined them with the text sparse features.
Then I'm feeding the algorithm to a gradient boosting model and doing the rest of the training and prediction. However I want to know, is there any way I can plot the feature importance, of this sparse matrix and will be able to know the important feature column names?
machine-learning python nlp feature-selection
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
$endgroup$
add a comment |
$begingroup$
I was working with a dataset which had a textual column as well as numerical columns, so I used tfidf for textual column and created a sparse matrix, similarly for the numerical features I created a sparse matrix using scipy.sparse.csr_matrix and combined them with the text sparse features.
Then I'm feeding the algorithm to a gradient boosting model and doing the rest of the training and prediction. However I want to know, is there any way I can plot the feature importance, of this sparse matrix and will be able to know the important feature column names?
machine-learning python nlp feature-selection
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
$endgroup$
I was working with a dataset which had a textual column as well as numerical columns, so I used tfidf for textual column and created a sparse matrix, similarly for the numerical features I created a sparse matrix using scipy.sparse.csr_matrix and combined them with the text sparse features.
Then I'm feeding the algorithm to a gradient boosting model and doing the rest of the training and prediction. However I want to know, is there any way I can plot the feature importance, of this sparse matrix and will be able to know the important feature column names?
machine-learning python nlp feature-selection
machine-learning python nlp feature-selection
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
asked 10 mins ago
Debadri DuttaDebadri Dutta
135
135
add a comment |
add a comment |
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