Questions tagged [text-classification]

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15 views

How to filter data samples which do not improve classifier?

I have a text dataset with noisy labels and an unbalanced shape. There are various ways to find features which do not drive improvement in some metric, and help to prune those from the pipeline. I ...
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1answer
10 views

How to improve LSTM accuracy on multiclass text classification?

So, I'm trying to build a LSTM model to classify multiclass text label. The goal is to make a prediction about user rating (1, 2, 3, 4, 5) based on their review. My hyperparameter is like this: ...
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How would you optimize this Binary Text Classification model further? The data set is large (40000 texts)

I'm learning about tensorflow/keras since a couple months. What are some methods to reduce overfitting in the later epochs or increase val. accuracy in general? train data dim (40000,70) (reddit ...
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25 views

Can one still train a classifier with an unbalanced data set?

I want to train a binary Naive Bayes classifier. The problem is, is that I have an unbalanced set at my disposal, where the ration between the two classes is roughly 2:1 (250 examples from the first ...
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2answers
19 views

Word list as a baseline for measuring a classifier's performance?

I am working on a simple Naive Bayes classifier that categorizes text messages as either "positive" or "negative". I was told that the simplest baseline to measure the classifier's ...
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17 views

How to write decider function for multiple models

I have trained two classifiers .. Text Classification and Image Classification. So both models gives score for each class. For example there are 3 classes. Each model give array of 3 confidence score ...
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1answer
22 views

Datasets for String Classification

I would like to test an experimental algorithm for string classification. More precisely, the dataset should be split into a set GOOD of good strigs and a set BAD of bad strings. The algorithm should ...
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1answer
21 views

How to identify the feature that make the model misclassifed in text classification

Hi I am working on social media financial THAI text classification, the problem with this one is the confused classes, the misclassified prediction has a pattern that consistent as a pair. and I want ...
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8 views

outdoor/indoor recognition in text

For a project I should train a model that predicts whether a certain text given as input (e.g the chapter of a book) is set indoor or outdoor. I do not have any labelled data. Could you point to ...
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15 views

What is the relation between the features of word-embeddings and the type of classifiers (linear or non-linear)?

I am doing an analysis on the results of classifiers (such as: linear SVM, RBF, Random forest, naive bayes and logistic regression) of a text classifcation problem using word-embeddings (I am using ...
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1answer
68 views

Sentence embeddings with LSTM to classify the sentences is not working

I am trying to build LSTM NN to classify the sentences. I have seen many examples where sentences are converted to word vectors using glove, word2Vec and so on here is an example of it. This solution ...
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1answer
50 views

Unsupervised Text Classification with Python: Kmeans

I am working on a project to build a text classifier of questions being asked. There are no labels provided in my data so I have chosen to go with an unsupervised approach. This solution needs to read ...
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1answer
28 views

Classification using texts as features

I want to build a classification model to match customers and products. I have a description of each product, and a description of each customer, and the label : ...
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23 views

Newspaper analysis

I'm currently working on a project, where I analyze newspaper articles about AI with NLP methods. My research question: Does newspaper coverage focus more on the advantages or disadvantages of AI? I ...
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16 views

Use Large Existing Dataset to Extract Information From Text

What I have: I have a large dataset of documents and their data. So I have the text of about 1M documents, and I know, for example the invoice number, of each one. What I need: Is there a way to use ...
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4 views

Identifying hierarchical structures from user submitted tags

I am working with a dataset of shops, where users have submitted some number (up to 5) of "tags" for each shop, which is supposed to describe an aspect of the shop. From the tags, I want to ...
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23 views

Training a Supervised Classifier using Continuous Data

I am trying to build a NLP classification model using methods such as XGBoost, SVM, logistic regression. The features I am trying to include are cosine similarity and LDA topic models, all of which ...
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2answers
32 views

How to train a model to predict if 2 samples refer to the same thing?

I have 2 ddbb with around 60.000 samples each. Both have the same features (same column names) that represent particular things with text or categories (turned into numbers). Each sample in a ddbb is ...
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12 views

Handling too much range in texts' length

I have a classification problem where inputs are news article and target are topics. However, articles length are very varying from 100 words to 800! I'm using TfIdf and I think that it can puzzle the ...
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16 views

Extracting structured data from semi structured data

I want to use machine learning and NLP to convert semi-structured data in text files to structured data by predicting the patterns in the files and splitting the fields for example if I have a text ...
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1answer
67 views

XLNET how to deal with text with more than 512 tokens?

From what I searched online, XLNET model is pre-trained with 512 tokens, and https://github.com/zihangdai/xlnet/issues/80 , I didn't find too much useful information on that either. How does XLnet ...
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12 views

How to interpret feature weight coefficients in logistic regression for text classification?

I am working on a simple text classification problem where I have as inputs tweets and as class whether that tweet contains fake news or not (0 is real news, 1 is fake news). I have trained a logistic ...
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37 views

Classifies the place of birth that belongs to the person at NER

I want to classify the place of birth and date of birth for each person detected by the NER results. For example, I have a sentence like this: This paper represents the fact that Jaden Smith was born ...
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11 views

How to train a text classifier for product search query to determine category

I am trying to train a product search query (e-commerce) classifier for deducing probable product categories from search query with a dataset of 700k queries with probable categories labelled I tried ...
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15 views

Extracting layer output from Classification model of SimpleTransformer

I have fine tuned a bert base model for text classification task. Now, I want to extract hidden layer output so as to combine this output with other features to train a random forest model. Problem ...
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27 views

How to train BERT (multi label) on imbalanced dataset for search query category classification

I have a dataset of 2 million search queries relative to 7000 categories. same query could have multiple categories. Aim is to predict category/categories for query with confidence score. I tried ...
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1answer
100 views

How to preprocess with NLP a big dataset for text classification

TL;DR I've never done nlp before and I feel like I'm not doing it in the good way. I'd like to know if I'm really doing things in a bad way since the beginning or ...
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26 views

Is my LSTM model overfitting or underfitting?

I am currently working on a project to classify comments text into 11 different topics, using a Bidirectional LSTM model. However, the loss curves confuse me as there is a deviation of the training ...
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1answer
23 views

How to calculate the “Evidence” for Naive Bayes text classification?

I'm trying to write a Naïve Bayes text classification from scratch in Python, but I can't quite grasp what I should do to write the actual classifier. One question that popped up was: "What ...
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1answer
16 views

Best approach to create a text classification model with two inputs?

I'm looking to train a model with two text inputs (sentences) and a binary classification. Essentially, for 2 given sentences, are they paraphrases or not. I want to use the Microsoft research ...
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1answer
24 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 ...
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27 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?
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23 views

Top-K vs AUC - communicating results and next steps [closed]

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 ...
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2answers
108 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}. ...
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41 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 ...
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43 views

Steps to perform multi label word classification

I am trying to classify small strings into three categories. Examples: ...
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11 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 ...
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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 ...
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1answer
48 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 ...
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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 ...
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67 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 ...
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1answer
33 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-...
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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 (...
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2answers
244 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 ...
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2answers
580 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: ...
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1answer
32 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 ...
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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 ...
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13 views

Converting a string to a recommendation type string

I am trying to build a recommendation system and some of the labels are ...
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1answer
22 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 ...