How to use a one-hot encoded nominal feature in a classifier in Scikit Learn?
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Im working on a genre classification problem on a songs dataset. Since genre is a nominal feature, I used sklearn's LabelBinarizer to get the one-hot encoding for this feature for every row in the dataset. I'm then left with a dataframe(df_train_num) with two columns, both numeric in nature and a Series object for which every row value is a numpy array - the one-hot encoding of the genre.I now want to fit a classifier on this data. What I did was:
svm_classifier = LinearSVC()
svm_classifier.fit(df_train_num,df_train_genre)
This gives me a ValueError: Unknown label type: 'unknown'
What exactly is causing this error? Am I not allowed to use a Series object with a DataFrame object in the to fit a classifier?Although replacing df_train_genre with df_train_genre.values so as to pass the numpy array directly to the fit method also doesnt change anything. Same error
Here is a view of the two pandas objects:
df_train_num.head(5)
Unique_Word_Count Sentiment Polarity
157277 126 0.027766
90109 114 -0.199545
106224 16 0.000000
221087 103 -0.058025
247082 409 -0.170143
df_train_genre.head(5)
157277 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
90109 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, ...
106224 [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
221087 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
247082 [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
Name: Genre_Encoded, dtype: object
machine-learning scikit-learn nlp pandas
asked 1 hour ago
Mudit JhaMudit Jha
1
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$begingroup$
Im working on a genre classification problem on a songs dataset. Since genre is a nominal feature, I used sklearn's LabelBinarizer to get the one-hot encoding for this feature for every row in the dataset. I'm then left with a dataframe(df_train_num) with two columns, both numeric in nature and a Series object for which every row value is a numpy array - the one-hot encoding of the genre.I now want to fit a classifier on this data. What I did was:
svm_classifier = LinearSVC()
svm_classifier.fit(df_train_num,df_train_genre)
This gives me a ValueError: Unknown label type: 'unknown'
What exactly is causing this error? Am I not allowed to use a Series object with a DataFrame object in the to fit a classifier?Although replacing df_train_genre with df_train_genre.values so as to pass the numpy array directly to the fit method also doesnt change anything. Same error
Here is a view of the two pandas objects:
df_train_num.head(5)
Unique_Word_Count Sentiment Polarity
157277 126 0.027766
90109 114 -0.199545
106224 16 0.000000
221087 103 -0.058025
247082 409 -0.170143
df_train_genre.head(5)
157277 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
90109 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, ...
106224 [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
221087 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
247082 [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
Name: Genre_Encoded, dtype: object
machine-learning scikit-learn nlp pandas
asked 1 hour ago
Mudit JhaMudit Jha
1
New contributor
Mudit Jha 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 |
$begingroup$
Im working on a genre classification problem on a songs dataset. Since genre is a nominal feature, I used sklearn's LabelBinarizer to get the one-hot encoding for this feature for every row in the dataset. I'm then left with a dataframe(df_train_num) with two columns, both numeric in nature and a Series object for which every row value is a numpy array - the one-hot encoding of the genre.I now want to fit a classifier on this data. What I did was:
svm_classifier = LinearSVC()
svm_classifier.fit(df_train_num,df_train_genre)
This gives me a ValueError: Unknown label type: 'unknown'
What exactly is causing this error? Am I not allowed to use a Series object with a DataFrame object in the to fit a classifier?Although replacing df_train_genre with df_train_genre.values so as to pass the numpy array directly to the fit method also doesnt change anything. Same error
Here is a view of the two pandas objects:
df_train_num.head(5)
Unique_Word_Count Sentiment Polarity
157277 126 0.027766
90109 114 -0.199545
106224 16 0.000000
221087 103 -0.058025
247082 409 -0.170143
df_train_genre.head(5)
157277 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
90109 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, ...
106224 [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
221087 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
247082 [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
Name: Genre_Encoded, dtype: object
machine-learning scikit-learn nlp pandas
asked 1 hour ago
Mudit JhaMudit Jha
1
New contributor
Mudit Jha is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
Im working on a genre classification problem on a songs dataset. Since genre is a nominal feature, I used sklearn's LabelBinarizer to get the one-hot encoding for this feature for every row in the dataset. I'm then left with a dataframe(df_train_num) with two columns, both numeric in nature and a Series object for which every row value is a numpy array - the one-hot encoding of the genre.I now want to fit a classifier on this data. What I did was:
svm_classifier = LinearSVC()
svm_classifier.fit(df_train_num,df_train_genre)
This gives me a ValueError: Unknown label type: 'unknown'
What exactly is causing this error? Am I not allowed to use a Series object with a DataFrame object in the to fit a classifier?Although replacing df_train_genre with df_train_genre.values so as to pass the numpy array directly to the fit method also doesnt change anything. Same error
Here is a view of the two pandas objects:
df_train_num.head(5)
Unique_Word_Count Sentiment Polarity
157277 126 0.027766
90109 114 -0.199545
106224 16 0.000000
221087 103 -0.058025
247082 409 -0.170143
df_train_genre.head(5)
157277 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
90109 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, ...
106224 [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
221087 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
247082 [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
Name: Genre_Encoded, dtype: object
machine-learning scikit-learn nlp pandas
machine-learning scikit-learn nlp pandas
asked 1 hour ago
Mudit JhaMudit Jha
1
New contributor
Mudit Jha is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 hour ago
Mudit JhaMudit Jha
1
New contributor
Mudit Jha is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 hour ago
Mudit JhaMudit Jha
1
New contributor
Mudit Jha is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 hour ago
Mudit JhaMudit Jha
1
asked 1 hour ago
Mudit JhaMudit Jha
1
1
New contributor
Mudit Jha is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Mudit Jha is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Mudit Jha 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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