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 6 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 6 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 6 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 6 mins ago
Debadri DuttaDebadri Dutta
135
asked 6 mins ago
Debadri DuttaDebadri Dutta
135
asked 6 mins ago
Debadri DuttaDebadri Dutta
135
asked 6 mins ago
Debadri DuttaDebadri Dutta
135
asked 6 mins ago
Debadri DuttaDebadri Dutta
135
135
add a comment |
add a comment |
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