TfIdf on pandas dataframe
I'm trying to do a text classifier and I want to apply tfidf on my dataset.It consists of a 20x20 matrix.On each column there are 20 documents(50.000 words each) of the same author.I'm reading the csv using pandas and then I'm trying to apply
TfidfVectorizer on my data.The problem is that it's quite slow and I'm wondering if it could be done faster.This is my approach:
results = np.array(400)
for author in authors:
results = np.append(results, list(data_set[author]))
tf_idf = TfidfVectorizer(sublinear_tf=True, norm='l2', min_df=0.3, max_df=0.75, encoding='latin-1', ngram_range=(1, 2), stop_words='english')
features = tf_idf.fit_transform(results)
I'm iterating over each column and append it to the results.I get a (400,) shaped numpy array(20 authors x 20 documents each = 400).It takes over one minute to finish(most of the time being spent in fit_transform method).Thank you!
python-3.x pandas numpy scikit-learn tfidfvectorizer
asked Nov 25 '18 at 9:31
AndreiAndrei
22
add a comment |
I'm trying to do a text classifier and I want to apply tfidf on my dataset.It consists of a 20x20 matrix.On each column there are 20 documents(50.000 words each) of the same author.I'm reading the csv using pandas and then I'm trying to apply
TfidfVectorizer on my data.The problem is that it's quite slow and I'm wondering if it could be done faster.This is my approach:
results = np.array(400)
for author in authors:
results = np.append(results, list(data_set[author]))
tf_idf = TfidfVectorizer(sublinear_tf=True, norm='l2', min_df=0.3, max_df=0.75, encoding='latin-1', ngram_range=(1, 2), stop_words='english')
features = tf_idf.fit_transform(results)
I'm iterating over each column and append it to the results.I get a (400,) shaped numpy array(20 authors x 20 documents each = 400).It takes over one minute to finish(most of the time being spent in fit_transform method).Thank you!
python-3.x pandas numpy scikit-learn tfidfvectorizer
asked Nov 25 '18 at 9:31
AndreiAndrei
22
add a comment |
I'm trying to do a text classifier and I want to apply tfidf on my dataset.It consists of a 20x20 matrix.On each column there are 20 documents(50.000 words each) of the same author.I'm reading the csv using pandas and then I'm trying to apply
TfidfVectorizer on my data.The problem is that it's quite slow and I'm wondering if it could be done faster.This is my approach:
results = np.array(400)
for author in authors:
results = np.append(results, list(data_set[author]))
tf_idf = TfidfVectorizer(sublinear_tf=True, norm='l2', min_df=0.3, max_df=0.75, encoding='latin-1', ngram_range=(1, 2), stop_words='english')
features = tf_idf.fit_transform(results)
I'm iterating over each column and append it to the results.I get a (400,) shaped numpy array(20 authors x 20 documents each = 400).It takes over one minute to finish(most of the time being spent in fit_transform method).Thank you!
python-3.x pandas numpy scikit-learn tfidfvectorizer
asked Nov 25 '18 at 9:31
AndreiAndrei
22
I'm trying to do a text classifier and I want to apply tfidf on my dataset.It consists of a 20x20 matrix.On each column there are 20 documents(50.000 words each) of the same author.I'm reading the csv using pandas and then I'm trying to apply
TfidfVectorizer on my data.The problem is that it's quite slow and I'm wondering if it could be done faster.This is my approach:
results = np.array(400)
for author in authors:
results = np.append(results, list(data_set[author]))
tf_idf = TfidfVectorizer(sublinear_tf=True, norm='l2', min_df=0.3, max_df=0.75, encoding='latin-1', ngram_range=(1, 2), stop_words='english')
features = tf_idf.fit_transform(results)
I'm iterating over each column and append it to the results.I get a (400,) shaped numpy array(20 authors x 20 documents each = 400).It takes over one minute to finish(most of the time being spent in fit_transform method).Thank you!
python-3.x pandas numpy scikit-learn tfidfvectorizer
python-3.x pandas numpy scikit-learn tfidfvectorizer
asked Nov 25 '18 at 9:31
AndreiAndrei
22
asked Nov 25 '18 at 9:31
AndreiAndrei
22
asked Nov 25 '18 at 9:31
AndreiAndrei
22
asked Nov 25 '18 at 9:31
AndreiAndrei
22
asked Nov 25 '18 at 9:31
AndreiAndrei
22
22
add a comment |
add a comment |
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