Questions tagged [labelling]
The labelling tag has no usage guidance.
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Labeling tool for ASR to either create audio or transcripts
Is there a labeling tool where I can create audio-transcription-pairs in both directions:
record audio for given text
create transcriptions for given audio?
What I have tried so far:
I went through ...
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multi label classifictaion - single class or group labels?
I currently working on a vehicle dataset, with the goal of detection and classification vehicle types (car, bus, truck, motorcycle).
In addition, for each vehicle, I want to detect and classify each ...
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post img labeling transformations
I am using labelImg.py (https://github.com/heartexlabs/labelImg) to label my training data set for a CNN I have (YOLOv4). in order to save on time, I would like to label all 400(ish) images, then ...
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Labelling large amounts of audio data in automatic or semi-automatic way
I am working on a project, where I have to label the audio datasets which has thousands of data, each audio data is for one second. I have to label where it is in idle or event happening or noise. I ...
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Sub labelling of an object
First timer in image processing - Pardon my cluelessness.
Is there a concept of sub labeling in objection identification? I want to label a person and sub label "eye" of a person and train a ...
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How to label legit users when trying developing a bot flagging classification model?
I’m working on a project where I try to flag bots from legit users on social media. The data I collected is not labeled but I have labeled about 17% of it (22k users) thought different techniques. ...
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too much data to label
I'm working on a Data Science project to flag bots on Instagram. I collected a lot of data (+80k users) and now I have to label them as bot/legit users. I already flagged 20k users with different ...
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Labelling a dataset for sentiment analysis, which model is the best?
I want to do some sentiment analysis on a large text dataset I scraped. From what I've learned so far, I know that I need to either manually label each text data (positive, negative, neutral) or use a ...
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Why label encoding before split is data leakage?
I want to ask why Label Encoding before train test split is considered data leakage?
From my point of view, it is not. Because, for example, you encode "good" to 2, "neutral" to 1 ...
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Unsupervised clustering for Text labelling
I have millions semi structured text descriptions of a job requirement.
Which needs to be labelled, such as the number of hours, years of experience required, shifts, certifications, licensure etc., ...
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CRFSuite/Wapiti: How to create intermediary data for running a training?
After having asked for and been suggested two pieces of software last week (for training a model to categorize chunks of a string) I'm now struggling to make use of either one of them.
It seems that ...
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Software/Library Suggestion: Is there a usable open-source sequence tagger around?
(Not sure if this is the right community for the question - please do downvote if stats. or whatever else is more appropriate...)
I'm looking for a suggestion for ...
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How should I construct a binary classifier for small set of positive data and million of unlabeled data?
Does anyone have suggestions for specific algorithm or implementation for labeled data of only one class and unlabeled data that can be from either classes? And I'm unsure what is the proportion of ...
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(Labeled, if possible) time-series datasets for anomaly detection [closed]
I would like to create a big list of available time-series datasets for anomaly detection. I'm especially interested in the following:
The time-series data should be segmented into cycles
Ideally, ...
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Sampling items from a population of subpopulations
I have a population of $n$ items to label and a budget to label only $m$ ($m << n$) of them before training. The population can be partitioned into subpopulations, recursively. In other words, ...
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Best practices to image annotation for object detection when objects overlap
If I have the following example:
How should I annotate the bottom image? I can think of those scenarios:
Create a large box that captures class B and a second box that captures entirely class A. ...
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Solutions for Labelling Training Data for Binary Classification Problems
I have a huge dataset for which I am trying to use an 80-20 (Holdout method) approach to train and test my model. However, the dataset I have been given has 6m rows. The objective is to train+test+...
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How do I label images faster
I have around 1600 images extracted from videos shot at night time. I am labeling each image and trying to be as accurate as I can in assigning bounding boxes. I am labeling vehicles and traffic light/...
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Online Audio annotation tools
I need to find a decent online annotation tool to transcribe audio.
There are some requirements for a potential tool:
I should be able to deliver audio files to a few labelers. I should
be able to ...
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Is an image with 5 labels equivalent to 5 images with 1 label?
I am collecting data to train an object detection model using and was wondering if 5 labels in the same image and 5 images with 1 label each provided the same quality of input training data. Example: ...
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Label A records B times or label A*B records
This question concerns pre-training data sourcing.
Suppose you have a human workforce of B individuals and a potentially unlimited source of data.
The task is ...
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How to pass more than 2 input columns to a Deep learning Keras model for sequence tagging/labeling
I have to build a neural network which extract relationship between two entities.Input should be:
Input text/paragraph, vocabulary of entities and relationship phrases that system should recognize.
...
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Python package for machine-learning aided data labelling
In a lot of cases unlabelled data needs to be transformed to labelled data. The best solution is to use (multiple) human classifiers. However, going to all the data by hand (i.e. in text-mining or ...
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