Questions tagged [text-classification]
The text-classification tag has no usage guidance.
116
questions
1
vote
1answer
16 views
What is a good approach for embedding both textual and spatial features for document classification?
I am working on a document classifier that can perform the classification based on the document structure as well. My plan is to get the word embedding as well as the word coordinates and somehow ...
0
votes
0answers
8 views
How to interpret feature importance in text classification using Fasttext?
Once the text is converted into a vector of size(1,100), how can we interpret and backtrace a word's importance which helped in classification?
1
vote
0answers
19 views
Top-K vs AUC - communicating results and next steps
I have a bi-LSTM multi-label text classification model which when training on a highly imbalanced dataset with 1000 possible labels gives a top-k (k=5) categorical accuracy of 86% and a focal loss of ...
1
vote
2answers
23 views
Multi-class classification with extremely small dataset
I am working on a text classification task that contains 216 labeled paragraphs. The distribution of tags is as follows:
{0: 17, 1: 15, 2: 16, 3: 9, 4: 10, 5: 18, 6: 24, 7: 9, 8: 33, 9: 38, 10: 27}.
...
0
votes
0answers
22 views
Detect action in email [closed]
I'm trying to detect a specific type of action intent in a marketing email email (e.g. a request for a free trial, or a recommendation to click on a link).
I have five types of intent I want to detect....
1
vote
0answers
23 views
NLP Subjectivity Detection methodology?
I am working on a project where I would like to be able to specifically analyze the level of subjectivity in a given text phrase using machine learning. Essentially, I would like to be able to ...
1
vote
0answers
40 views
Steps to perform multi label word classification
I am trying to classify small strings into three categories.
Examples:
...
0
votes
0answers
10 views
Can a term weighting function used in text retrieval be compared to one used in text classification?
I came up with a modified version of TF-IDF function for text retrieval task. I want to do retrieval experiments using Vector Space Model and compare my function to some of those proposed in the ...
1
vote
0answers
10 views
auto updating text comparison model
I have a need to create a model that compares and groups distinct snippets of text based on keywords. I can extract similar keywords with NLP methods and simply comparing sentence text. I want these ...
1
vote
1answer
40 views
Classify tweets by topic [closed]
I am approaching machine learning for the first time because of my studies. I have been given a bunch of tweets and the goal is to classify them per topic. I really have no clue on how this should be ...
1
vote
1answer
19 views
Matching Data Text of Two Place with Exception [closed]
I have data of two places name and it's address in a row and i have to match it. Data is text type, I have read, it have to convert to numeric type that generated by the text. I extracted the numeric ...
1
vote
0answers
62 views
Sklearn - multiclass text classification
I took a challenge to classify bugs (by scanning their logs) into a different groups (classes).
I've already accomplished part of the task by fetching + cleaning the data, but I'm now stuck on getting ...
0
votes
0answers
16 views
Classification report results: low values in precision and f1-score
I am familiarising with new concepts as classes imbalance in ML.
Applying an algorithm (log regression) to my dataset which include fake/not fake news, I have got the following classification report:
<...
0
votes
1answer
25 views
How to use scikit-learn to extract features from text when I only have positive and unlabeled data?
I'm looking for something similar to this
https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#sphx-glr-auto-examples-text-plot-document-classification-...
1
vote
1answer
14 views
Understanding the XLNet model for a concrete case
I'm a data science student, recently I reviewed the XLNet paper and I have a doubt about it:
Imagine we are using many categories, let's say 200, can this model has problems reaching a good accuracy (...
3
votes
2answers
109 views
Effect of Stop-Word Removal on Transformers for Text Classification
The domain here is essentially topic classification, so not necessarily a problem where stop-words have an impact on the analysis (as opposed to, say, sentiment analysis where structure can affect ...
3
votes
2answers
568 views
Over-sampling: is my model over-fitting?
I would like to ask you some questions on how to consider (good or not) the following results:
...
1
vote
1answer
26 views
Optimal input setup for character-level text classification RNN
I want to classify 500-character long text samples as to whether they look like natural language using a character-level RNN. I'm unsure as to the best way to feed the input to the RNN. Here are two ...
0
votes
1answer
20 views
Which are the worse machine learning models for text classifications? [closed]
I was looking at text classification, and for curiosity I was searching online for which were the best models for text classifications. About this, I found that they are linear support vector machines ...
0
votes
0answers
13 views
Converting a string to a recommendation type string
I am trying to build a recommendation system and some of the labels are
...
0
votes
1answer
20 views
the models in deep-learning on a little corpus
I have a little corpus (around 450 observations with approximately 50 words) with domain specific words. I have to classify each observation with a target variable with 5 classes. I tokenized and did ...
1
vote
0answers
36 views
SVM on BERT-Embeddings with very small dataset does not converge
I am trying to reproduce the results from this paper where they use a linear SVM on top of BERT-Embeddings for text-classification. They use the average of the token-embeddings which results in a 768 ...
1
vote
1answer
47 views
Public dataset for news articles with their associated categories for multilabel data classification
I am wondering if there are any public datasets of news, like New York Times (NYT) or similar to various news categories such as politics, entertainment, lifestyle, general news, sports etc.
I want to ...
0
votes
0answers
53 views
How to find parts of text that answer a “why”
Given some text that describes something,
how to tag / identify parts of the text
that explain specific aspects - what, who, why?
For example, given the following input text...
...
1
vote
0answers
11 views
Discovering important topics in corpus of text using metadata and text content
I am working on a system to classify documents into important/non-important. I have a large (200,000) sample set of documents which have been pre-labelled and using Naive-Bayes I have achieved 95% ...
0
votes
1answer
32 views
Train and Test Data Split for a Tweet Classification Task
I am trying to train a few Machine Learning (ML) algorithms such as SVM, NB and Random Forest to do binary classification on disaster tweets. During this project, I want to train ML algorithms for a ...
2
votes
1answer
23 views
Bug in sentiment analysis and classification for unlabeled text [closed]
I'm working on the transcript of Trump and Biden's debate and want to analyze the sentences and classify negative, positive, or neutral comments, but I ran into one problem. I used both TextBlob and ...
1
vote
1answer
30 views
Understanding the generality of the NER problem
Named-entity recognition (NER) is a well-known problem in the NLP literature.
It typically addresses the problem to locate and classify named entities in text, e.g. ...
2
votes
0answers
22 views
Does Keras allow using independant classifier
I have spam data set classified into 0:ham or 1:spam. I created the Embedding layer with Keras and then I used Conv1D following with other layers. My question is about adding a classifier like Random ...
1
vote
1answer
14 views
Grouping profiles strings having the same words, but occurring out of order
I have a dataframe containing a column of profile types, which looks like this:
...
3
votes
1answer
28 views
Predictive output with your own model built
I would need to better understand how can be created a machine learning algorithm from scratch using an own model developed based on boolean values, for example # of words in a text, # of punctuation, ...
1
vote
0answers
27 views
How can I make a better unsupervised text classifier model? Is POS tagging part of Machine Learning and Data science?
I have got complaints data, which is not good, and often contains less than 3 words in every complaint (sometimes so short that only one word of them makes sense). The objective is to find what's ...
2
votes
1answer
64 views
Is there a way to classify an alphanumeric string? [closed]
I have data containing various items. Each item has a unique alphanumeric code associated with it (see the example below).
Is there a way to predict the item type based on the alphanumeric code?
Data:
...
0
votes
3answers
41 views
Distinguish randomly generated texts from reasonable for human texts [closed]
I have strings short texts of 2 types:
'23jd2032n0d2mn', 'fn830n30rn83', 'fhui29n4ok', 'qn4foml', ...
and
...
0
votes
1answer
33 views
How can a ML algorithm learn to classify fake news? [duplicate]
I am new in Machine learning techniques and in fake news detection by using these algorithms (SVM, nn, logistic regression,..).
I would like to understand how an algorithm can learn from a training ...
0
votes
0answers
14 views
Classify Spanish Text into different Categories
I want to recommend articles to users depending upon what type of article is user reading, Music, Movies, Politics, etc.
I have 3 features: Page Title, Labels, article content.
I am using an API (...
0
votes
1answer
37 views
Ordering of standardization, pca, and/or tfidf for neural network
I have 60k rows of text data. I have tokenized it into 55k columns. I am using a neural network to classify the data but have some questions about how to order my preprocessing steps. I have too much ...
1
vote
0answers
14 views
Trying to use CBOW for tweet classification
I'm trying to use the Continuous Bag Of Words method for word embedding on a corpus of 7503 tweets.
In particular, I'm trying to use CBOW on this Kaggle competition, which involves classifying tweets ...
4
votes
1answer
90 views
How to include categorical fields to enhance a text classification
I would have a question on how to add more categorical fields in a classification problem.
My dataset had initially 4 fields:
...
0
votes
1answer
26 views
Is it possible to classify documents of corpus using labels?
I have a corpus of 23000 documents that need to be classified into 5 different categories. I do not have any labeled data available to me, just freeform text documents and labels(yes, one-word labels, ...
0
votes
1answer
23 views
How to categorize unlabelled promotional email data
I have unlabelled data of promotional emails. I want to categorize those emails based on the topics like fashion, health & wellness, sports, media, Entertainment, etc. Can anyone let me know any ...
2
votes
1answer
23 views
Interpreting confidence interval results for datasets
I have created a dataset automatically and wanted to clarify my interpretation of the amount of noise using the confidence interval.
I selected a random sample and manually annotated the sample and ...
0
votes
1answer
38 views
Classifiers and accuracy
I would like to ask you how to use classifier and determine accuracy of models.
I have my dataset and I already cleaned the text (remove stopwords, punctuation, removed empty rows,...).
Then I split ...
1
vote
1answer
55 views
Sampling in Text Classification: can the results be considered 'reliable'?
I am testing different models (SVM, Logistic Regression, Naive Bayes, Random Forest) for predicting the class of a spam email. My target is a binary variable.
I am analysing only text, no other fields....
0
votes
1answer
21 views
How to create a Document Categorization Classifier for different contexts of Documents
I have a doubt solving a test. The idea here is to demonstrate the NLP and Machine Translation abilities.
The Dataset is a multilingual, multi-context set of documents. The dataset is divided on ...
1
vote
2answers
40 views
Problem of continuous training - Supervised learning
I am sure this is a most common problem, but would like to know by experts on how to tackle it. Note that, I mostly deal with textual data (NLP problems).
When a supervised learning model is created, ...
1
vote
1answer
39 views
Creating a valid dataset for obtaining results
I have created a domain-specific dataset, lets say it is relating to python programming topic posts. I have taken data from various places specific to this topic to create positive examples in my ...
0
votes
0answers
17 views
How to approach a text parsing problem
I'm looking to parse human-generated cyber-physical sensor tags into a series of standardised tags and identifiers.
For example "Rm3.ZnT-SP" refers to ROOM ID:3 ZONE TEMPERATURE SETPOINT
The ...
2
votes
1answer
56 views
Any useful tips on transfer learning for a text classification task
I am doing a supervised binary text classification task.
I want to classify the texts from site A, site B, and site C.
The in-domain performance looks OK for texts of each site. (92%-94% accuracy).
...
0
votes
1answer
20 views
(Serious) Dataset of paedophilic Youtube comments (or similar)? [closed]
I think it would be useful to create a model that tries to predict whether a youtube comment is paedophilic - maybe the model should also take into account the channel name/description/front image.
It'...
