Questions tagged [text-classification]
For questions about text classification, the task of assigning predefined categories (or classes) to free-text documents.
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Using a fine-tuned model for a different dataset
I have a dataset of different sentences from news articles which I need to classify by their sentiment. For that goal I'm planning to use a fine-tuned model which was fine-tuned on different datasets, ...
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Is there anyway to classify the category on give amazon reviews using python
I am trying to find a model or way to classify text which falls into a category and its a positive or negative feedback.
For ex. we have three columns
Review : Camera's not good battery backup is not ...
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Contextual word embeddings from pretrained word2vec vectors
I would like to create word embeddings that take context into account, so the vector of the word Jaguar [animal] would be different from the word Jaguar [car brand].
As you know, word2vec only gives ...
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Can i use Transformer-XL for text classification task?
I want to use transformer xl for text classification tasks. But I don't know the architect model for the text classification task. I use dense layers with activation softmax for logits output from the ...
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Language Detection using pycld2
I am trying to use the pycld2 package to detect multiple languages in text. This package provides Python bindings for the Compact Language Detect 2 (CLD2)
This is the example I am testing out:
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Suggestions for a multi-class text classification model with a large number of classes?
I was working on a text classification problem where I currently have around 40-45 different labels.
The input is a text sentence with a keyword. For e.g. ...
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Ideal Windows Size in Pk Evaluation Metric
I am very new to nlp. I am doing a text segmentation task and for evaluating my model I need to calculate Pk and Windiff scores. My question is what is the ideal value for window size (k) for Pk score ...
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Naive Bayes TfidfVectorizer predicts everything to one class
I'm trying to run Multinomial Bayes classificator on various balanced data sets and comparing 2 different vectorizers: TfidfVectorizer and CountVectorizer. I have 3 classes: NEG, NEU and POS. I have ...
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sentence type classification
I want to classify the sentences in my dataset as declarative, interrogative, imperative and ...
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predictive effect in the classification made according to the comments in different fields
I want to do a classification through comments categorized in 4 areas(X,Y,Z,M). Categorizing the product as good or bad based on the comments in the fields X, Y, Z, M. How can I follow a path to see ...
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How can I implement text classification for this problem?
Given a collection of documents - each corresponding to some economic entity - I am looking to extract information and populate a table with predetermined headings. I have a small sample of this ...
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How to provide Intentional Bias towards recent examples in Text Classification?
I have trained an XGBClassifier to classify text issues to a rightful assignee (simple 50-way classification). The source from where I am fetching the data also provides a datetime object which gives ...
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Multi-Class Document Classification with both known and un-known classes
Currently, I am building a multi-class document classifier which has to classify either 3 known classes, namely "Financial Report", "Insurance_Sheet", "Endorsement", and ...
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Commercial product name classification with product id
I want to give the probability of how the entered name (user 1) for product X matches with the names (historical names from all users) of product X.
I have data with the following structure:
while ...
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Deep Regression Ensembles(DRE) - text analysis
I read an article about Deep Regression Ensembles(DRE), which can outperform DNN using SDG.
My question is could I use DRE in text classification? (for example, I can use it instead of LDA) What about ...
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How to down\up sample text?
I have data set of 5566 samples - one column is the text of the recipe description and the other is what tax class is it.
I wish to make a classifier that would classify receipts using ML only.
I have ...
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Removing footers from text scraped from news sites
I am wondering if anyone knows of libraries out there that will remove footer material from text scraped from news sites, like the material in italics below:
“Go, I’ll catch up with you,” the woman ...
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Text segment identification without clear boundaries
I am considering the problem of creating a supervised machine learning algorithm able to identify segments of text that are of interest, but where the segments will not, in general, coincide with a ...
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Training a model with a series of text responses as input
I want to train a binary classifier on text -- so something like sentiment analysis, but my input vectors are going to be a series of responses from some user separated by some separator character. I ...
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What are the exact differences between Word Embedding and Word Vectorization?
I am learning NLP. I have tried to figure out the exact difference between Word Embedding and Word Vectorization. However, seems like some articles use these words interchangeably. But I think there ...
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A multi label text classification problem
I'm looking to solve a multi label text classification problem but I don't really know how to formulate it correctly so I can look it up.. Here is my problem :
Say I have the document ...
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Distinguishing text with opposite meanings in SVM (False Information Detection)
I am currently working on a Binary Text Classification Model (False Information Detection) using Support Vector Machine and used TF-IDF as text vectorizer in Python. I have already tried training the ...
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How to identify the limiting factor in my text classification model?
I am working on building a comments classification model, with about 2500+ comments (varying in length from 5 to ~110 words) and 11 categories (yes I understand the ratio is quite bad). So far, I have ...
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Understanding how Long Short-Term Memory works in classification of sequences of symbols
I want to use a LSTM neural network to classify sequences of protein according to the host species. For example, I have these sequences of letters (toy example, just to understand):
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Getting the keywords of text classification prediction in real time
I am using a BERT based text classification model to classify sentences/documents. My use case is like I need to highlight the words that are responsible for classification of a particular class. This ...
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Model Overfitting in text classification how to solve?
This is my CNN model i am doing text classification on mental health social media data. the model is overfitting as validation loss is much greater than training loss.
There are three columns(Text, ...
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How to select a proper vectorization method in NLP?
Suppose we have a text classification problem.
As we all know we have to convert the text data into vectors so as to train the model. So there are a couple of vectorization methods such as count ...
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Can mean-shift clustering algorithm be used for text clustering?
Mean Shift clustering is an Unsupervised learning that assigns the data points to the clusters iteratively by shifting points towards the mode (mode is the highest density of data points in the region,...
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String Matching Classification and Scoring
I've been playing with a problem around matching product names. I've trained a model based on a variety of different features (numbers only, Levenshtein distance, pulling out package sizes, brands, ...
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How to get fine-grained sentiment score from text data under unsupervised learning?
In my experience I have only used LSTM models to do sentiment classification tasks on text data under supervised learning. For example, the imdb dataset from keras which is a binary classification ...
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Best practices to train a transformer text classifier to predict/handle unseen labels
I fine-tuned a RoBERTa sequence classifier to classify paragraphs of certain documents using labeled paragraphs only (and skipping paragraphs with no label given). The model was validated and tested ...
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Classification Texte with naive bayes complement
Currently I am on a text classification project, the goal is to classify a set of CVs according to 13 classes. I use the bayes algorithm (ComplementNB), in my tests it is the model that gives the ...
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Calculating customer satisfaction based on call transcripts
I have a massive dataset of call center transcripts and I want to rate them on a scale of 1-10 based on customer satisfaction. What’s the best way to go about that?
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Neural Network output recognition
In my environment, I have an LSTM network that has been trained to perform text generation using an input pattern string and a given dataset of words. Now I am facing a problem: it would be possible ...
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How to generate syntactically correct text for CRNN-CTC text model?
Disregarding the image creation and labeling details, is there a way to generate syntactically correct text examples? As of my current understanding of the CTC model, it takes into consideration the ...
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Tensorflow text classification in R using 3 classes - Error in py_call_impl(callable, dots\$args, dots\$keywords)
I'm working on a text classification problem that classifies some tweets into one of three labels. I have two columns in my dataset: Score column with the value of 0 (negative), 1 (positive) or 2 (...
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How to use TfidfVectorizer on dataframe
I have the dataframe which has 3 colums(Positive Reviews, Negative and Score):
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validation/test set uniqueness question
Hopefully a simple question, but it's a little unclear to me on how best to separate train/validate/test sets.
I have say 100 examples of class A. I'm classifying text into either class A, which I ...
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How to evaluate triple extraction in NLP?
I am current NLP work, I am extracting triples using triple extraction function in Stanford NLP and Spacy libraries. I am looking for a good method to evaluate how good the extraction has been? Any ...
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Is there any method to separate text into paragraphs of similar context
I want to split my text that has various sentences of different context mixed into separate paragraphs of similar context.
for example, if my text is:
...
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Text classification length
I have a set of text examples I need to learn as class A, and they are of varying lengths, say 10 sentences to 1 sentence long. I have to parse a document to find those strings of text that match one ...
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Is binary classification the right choice in this case?
I am somewhat new to text classification and I have some questions if you folks can help:
I have some text I need to be able to classify as belonging to a single class or not (usually 1-10 sentences ...
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pcap post request body string classification [closed]
I want to classify malware traffic. I am going to use the machine learning method to classify the post request body string in the pcap file. The conventional text classification algorithm may not work ...
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What are the best ways to convert different parts of speech to noun?
I am working on a topic modelling task. I want to convert different parts of speech such as adjectives, verbs to noun. What are the best ways of doing this? I have tried lemmatization using NLTK ...
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Imbalanced NLP text classification
I'm trying to solve a multi-class text classification task with 3 classes. I have an initial pretty balanced but small dataset. When I start to mine additional data I can't always find a lot of new ...
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Questions of understanding - Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation
I'm currently analysing the paper Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation (Post, Vilar 2018): https://arxiv.org/abs/1804.06609
I have ...
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Automatically finding business opportunities in text documents
I am new to machine learning and NLP.
I am exploring the possibility of using one of these approaches to automatically examine a large collection of text documents and determine, first of all, if they ...
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Any transformer model (NLP) for code classification?
Does any Transformer (NLP) that is suitable for code classification tasks exist?
For example, I have a lot of source codes of various categories (driver, game, email client, etc.). I want to ...
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Handwritten Text Recognition with different char set
I was trying to understand how Handwritten Text Recognition works but here I am. I did a lot of research but still, I couldn't exactly understand how will HTR architectures work even with different ...
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Classification issues with Binary Sentiment analysis
I am trying to conduct a binary sentiment analysis of Arabic text (i.e. either classifying social media posts into negative/positive). I built a basic dictionary that covers all words included in the ...
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