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TDIF toarray() returns an array of zeros
Features of word vectors in word2vecWhat is the difference between a hashing vectorizer and a tfidf vectorizerUsing TF-IDF with other features in SKLearnIdf values of English wordsSklearn tfidf vectorize returns different shape after fit_transform()Naïve Bayes and Training DataKDE on TF-IDF - sensitive bandwidthMixing Textual Data and Numerical Data (Neural Network)Pipeline with linearSVM and LSTMMy naive (ha!) Gaussian Naive Bayes classifier is too slow
$begingroup$
radius = tvec.fit_transform(test_df.Tweet_lemmatized)
c=tvec.get_feature_names()
print(radius)
This returns the correct values, but when i try to convert it to array, i get an array of zeros instead.
sample of correct values for radius:
(0, 931) 0.46436660485060216
(0, 861) 0.2968833582955266
(0, 484) 0.41499526789066504
(0, 363) 0.3991012474411105
(0, 560) 0.46436660485060216
(0, 1300) 0.3861148871586334
(1, 861) 0.31024421676439334
(1, 1252) 0.38207837156371705
(1, 935) 0.2915380548059053
(1, 894) 0.4852648341103948
(1, 299) 0.4550847285244575
(1, 670) 0.2766014729498025
(1, 1250) 0.3920175536236695
(2, 861) 0.30814515003485
but radius.toarray() and radius.todense() returns:
[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]
radius.shape is (498, 1776)
sentiment-analysis tfidf
asked 10 mins ago
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$endgroup$
add a comment |
$begingroup$
radius = tvec.fit_transform(test_df.Tweet_lemmatized)
c=tvec.get_feature_names()
print(radius)
This returns the correct values, but when i try to convert it to array, i get an array of zeros instead.
sample of correct values for radius:
(0, 931) 0.46436660485060216
(0, 861) 0.2968833582955266
(0, 484) 0.41499526789066504
(0, 363) 0.3991012474411105
(0, 560) 0.46436660485060216
(0, 1300) 0.3861148871586334
(1, 861) 0.31024421676439334
(1, 1252) 0.38207837156371705
(1, 935) 0.2915380548059053
(1, 894) 0.4852648341103948
(1, 299) 0.4550847285244575
(1, 670) 0.2766014729498025
(1, 1250) 0.3920175536236695
(2, 861) 0.30814515003485
but radius.toarray() and radius.todense() returns:
[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]
radius.shape is (498, 1776)
sentiment-analysis tfidf
asked 10 mins ago
IvyIvy
1
New contributor
Ivy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
radius = tvec.fit_transform(test_df.Tweet_lemmatized)
c=tvec.get_feature_names()
print(radius)
This returns the correct values, but when i try to convert it to array, i get an array of zeros instead.
sample of correct values for radius:
(0, 931) 0.46436660485060216
(0, 861) 0.2968833582955266
(0, 484) 0.41499526789066504
(0, 363) 0.3991012474411105
(0, 560) 0.46436660485060216
(0, 1300) 0.3861148871586334
(1, 861) 0.31024421676439334
(1, 1252) 0.38207837156371705
(1, 935) 0.2915380548059053
(1, 894) 0.4852648341103948
(1, 299) 0.4550847285244575
(1, 670) 0.2766014729498025
(1, 1250) 0.3920175536236695
(2, 861) 0.30814515003485
but radius.toarray() and radius.todense() returns:
[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]
radius.shape is (498, 1776)
sentiment-analysis tfidf
asked 10 mins ago
IvyIvy
1
New contributor
Ivy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
radius = tvec.fit_transform(test_df.Tweet_lemmatized)
c=tvec.get_feature_names()
print(radius)
This returns the correct values, but when i try to convert it to array, i get an array of zeros instead.
sample of correct values for radius:
(0, 931) 0.46436660485060216
(0, 861) 0.2968833582955266
(0, 484) 0.41499526789066504
(0, 363) 0.3991012474411105
(0, 560) 0.46436660485060216
(0, 1300) 0.3861148871586334
(1, 861) 0.31024421676439334
(1, 1252) 0.38207837156371705
(1, 935) 0.2915380548059053
(1, 894) 0.4852648341103948
(1, 299) 0.4550847285244575
(1, 670) 0.2766014729498025
(1, 1250) 0.3920175536236695
(2, 861) 0.30814515003485
but radius.toarray() and radius.todense() returns:
[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]
radius.shape is (498, 1776)
sentiment-analysis tfidf
sentiment-analysis tfidf
asked 10 mins ago
IvyIvy
1
New contributor
Ivy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 10 mins ago
IvyIvy
1
New contributor
Ivy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 10 mins ago
IvyIvy
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Ivy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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asked 10 mins ago
IvyIvy
1
asked 10 mins ago
IvyIvy
1
1
New contributor
Ivy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Ivy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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Check out our Code of Conduct.
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