Questions tagged [text-classification]

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What is the state of the art solution for text classification for large corpora

I have a need to classify documents in a set of documents, which grows over time from a small tagged training set. The classification is a binary classification. Training on the tagged set produces ...
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22 views

Time distributed word position prediction

I am facing the following problem. I need to create a model to predict the product groups from product title. For each word in sentence I need to predict position of a word marked as product. My ...
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1answer
48 views

Is it possible that every class has a higher recall than precision for multi-class classification?

I am a student learning machine learning recently, and one thing is keep confusing me, I tried multiple sources and failed to find the related answer. As following table shows (this is from some paper)...
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1answer
24 views

Text classification of non-equal length texts, should I pad left or right?

Text classification of equal length texts works without padding, but in reality, practically, texts never have the same length. For example, spam filtering on blog article: ...
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27 views

accessible subset of data impacts performance

I have a problem with a subset of my data which is as follows: I can train a model (doesn't matter what, xgboost, BERT, etc., it is a text classification problem), on my data and get a decent ...
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1answer
29 views

NLP Identifying important key words in a corpus

I am intrigued with the idea of Zettelkasten but unsatisfied with the current implementations. It seems to me that a machine learning and NLP approach could be productive by helpfully identifying “...
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26 views

My LSTM text classification model seems not learn anything in early epochs

I am trying to use LSTM to do text classification and monitor the training process with tensorboard. But it seems that this model doesn't learn anything in early epochs. Is it normal for LSTM networks?...
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40 views

Applications of polar decomposition in Machine Learning

Assume there exists a new and very efficient algorithm for calculating the polar decomposition of a matrix $A=UP$, where $U$ is a unitary matrix and $P$ is a positive-semidefinite Hermitian matrix. ...
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0answers
15 views

How many spectrogram frames per input character does text-to-speech (TTS) system Tacotron-2 generate?

I've been reading on Tacotron-2, a text-to-speech system, that generates speech just-like humans (indistinguishable from humans) using the GitHub https://github.com/Rayhane-mamah/Tacotron-2. I'm very ...
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30 views

Creating Text Features using word2vec

My task is to classify some texts. I have used word2vec to represent text words and I pass them to an LSTM as input. Taking into account that texts do not contain the same number of words, is it a ...
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4answers
84 views

Top Frequent occurrence word effect in Model Efficiency?

Assume that I have a Dataframe with the text column. Problem: Classification / Prediction ...
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1answer
43 views

Can artificial intelligence classify textual records?

I am a records manager and I am being asked if I recommend Office 365. I'm having a hard time making a recommendation because I am missing an essential piece of information: can Office 365 replace ...
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35 views

Are bayesian neural networks suited for text (or document) classification?

I've tried to do my research on Bayesian neural networks online, but I find most of them are used for image classification. This is probably due to the nature of Bayesian neural networks, which may be ...
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43 views

Pre-trained Models for Topic Modelling Transfer Learning (LDA)

I've been searching online - and so far, I've been unable to find any publicly-accessible pre-trained models that can be used for LDA Topic Modeling - Transfer Learning. Can anyone share any resources ...
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30 views

Tensorflow based implementation of Text classification with any variation of BERT(ALBERT/XLNET)

Do you have any reference you can point me to for doing Text classification using any variation of BERT(albert or XLnet) with a TF implementation. I am not sure how to deploy torch based models, so ...
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1answer
42 views

Is it possible to derive meaning from text by providing multiple ways of saying the same thing to a neural network?

Let's say I feed a neural network with multiple string sentences that mean roughly the same thing but are formulated differently. Will the neural network be able to derive patterns of meaning in the ...
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0answers
17 views

Language Learning feedback with AI

Is there a program under development that uses AI technology, like Siri, to "hold hands" so to speak with a language learner and coach them on accent, colloqiual expressions, or to let them guide the ...
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1answer
50 views

When is it time to switch to deep neural networks from simple networks in text classification problems?

I did an out of domain detection task (as a binary classification problem) and tried LR and Naive Bayes and BERT but the deep neural network didn't perform better than LR and NB. For the LR I just ...
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17 views

Text detection on English and Chinese language

https://arxiv.org/abs/1910.07954 In this paper, we have a convolutional character neural network where we have object detection by taking a character as a basic unit. First, we do character detection ...
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1answer
42 views

How does the weight update formula for logistic regression work?

I am trying to use Logistic Regression to make a spam filter, but I am having trouble understanding the weight update part. I have processed my email dataset, and I have an attribute vector of the top ...
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2answers
75 views

Does summing up word vectors destroy their meaning?

For example, I have a paragraph which I want to classify in a binary manner. But because the inputs have to have a fixed length, I need to ensure that every paragraph is represented by a uniform ...
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1answer
29 views

How can a system recognize if two strings have the same or similar meaning?

How can a system recognize if two strings have the same or similar meaning? For example, consider the following two strings Wikipedia provides good information. Wikipedia is a good source of ...
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2answers
61 views

Is there any classifier that works best in general for NLP based projects?

I've written a program to analyse a given piece of text from a website and make conclusary classifications as to its validity. The code basically vectorizes the description (taken from the HTML of a ...
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2answers
117 views

How to use LSTM to generate a paragraph

A LSTM model can be trained to generate text sequences by feeding the first word. After feeding the first word, the model will generate a sequence of words (a sentence). Feed the first word to get the ...
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1answer
1k views

What is the most accurate pretrained sentiment analysis model by 2019?

I've been using OpenAI's 2017 Sentiment Neuron implementation (https://github.com/openai/generating-reviews-discovering-sentiment) for a while, because it was easy to set up and was the most accurate ...
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0answers
60 views

Focal loss for imbalanced multi class classification in Pytorch

I want an example code for Focal loss in PyTorch for a model with three class prediction. My model outputs 3 probabilities. ...
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0answers
53 views

How to train LSTM score prediction with very little data? (Bounty to be added)

I am trying to make a text score prediction network, and my dataset have 500 samples only. I know there is a public dataset called the ASAP Dataset. I have tested my model ...
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1answer
214 views

Is a dataset of roughly 700 sentences of an average length of 15 words enough for text classification?

I'm building a customer assistant chatbot in Python. So, I am modelling this problem as a text classification task. I have available more or less 7 hundred sentences of an average length of 15 words (...