Questions tagged [labels]
Use for questions about the labels associated with the ground-truth of a dataset. Typically these data points have been labelled by a domain expert and can therefore be assumed to be true, against which we can compare the predictions of our algorithms.
105
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How to compare labels from clustering analysis and original ones?
I was asked to run a clustering analysis to assess the validity of labels for a manually labelled dataset.
I can simply save the actual labels (4 classes: 0, 1, 2, 3) and run clustering analysis (let'...
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6
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How to change label values in mask image
I have a mask image, where 0,10,20,30 are the labels assigned to the image. I want to change that value to 0,1,2,3 for multiple images.
0 - background
10- Building
20- Forest
30- Road
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1
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151
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How to predict on data that is label encoded as end user will input a categorical data?
My dataset contains about 29 features with 3 class labels as result. Among these 29 features around 24 features are categorical i cannot transform each category into numbers as there are many more ...
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28
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Is my image too low res for semantic segmentation task?
I am trying to solve a semantic segmentation task in the field of agriculture and I have some ortophoto drone images that have been acquired at the same height above the crops and in different ...
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9
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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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147
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Evaluate predicted values compared with labels and actual value
I have generated a range of predicted data. I also have the label and an actual representation of the data. How do I evaluate if my predicted data is any good?
The predicted value represents the ...
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0
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21
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Supervised recommender system design feedback
I am facing a challenge that I am not quite sure how to solve and would like to hear feedback.
Basically, I have to implement a recomendation system for certain courses to be recommended to users of ...
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9
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Weakly supervised learning with a set of candidate labels
I have a weakly supervised learning scenario where for every training example, there's multiple candidate labels. Only one of these candidate labels is the actual ground truth.
I.e. it's a typical ...
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33
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Label network embedding as input features for multi-label classification
Leveraging correlation between labels is an essential aspect of multi-label classification. I am trying to figure out the best approach for incorporating label correlation information for my task. One ...
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1
answer
91
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Using k-means to create labels for supervised learning
I want to know if the following is a valid approach to create labels, if I have measurements under some conditions, and the conditions are similar but never exactly the same.
This doesn't correspond ...
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1
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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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11
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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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0
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55
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Are more target labels in a multi-label classification always better?
Context
We work on medical image segmentation. There are a lot of potential labels for one and the same region we segment. There can be different medically defined labels like anatomical regions, more ...
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1
answer
232
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How to use confidence labels?
I have 2 sets of training data in csv files. The training data have class labels, 1 for memorable, and 0 for not memorable. In addition, there is also a confidence label for each sample. The class ...
user135529
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1
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58
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Using CNNs to detect incorrect label images in dataset
What I want to do is to train a model to identify the images that are incorrectly labeled in my dataset, for example, in a class of dogs, I can find cats images and I want a model that detects all ...
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66
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Labelling for churn measurement
I have 3 domains of supplier data (Jan 2017 to Jan 2022) and they are as follows
a) Purchase data - Contains all the purchase (of product) data made by the suppliers with us. It contains columns such ...
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2
answers
50
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Given daily sequence of events with only event ID labels (alphanum strings), what algorithms can be used to detect sequences that are outliers?
For example, the data might be something like this:
...
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1
answer
14
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Ordered categorical xlabel number - what to call xlabel
Say I have 105 brand names from a store, and I know the average retrun percentage for the products of the different brands. .
For example:
...
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1
vote
1
answer
39
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Supervised vs Unsupervised - Flag fake accounts on social medias
I have this project I'm working on where I scraped users' data from social media to predict if they are bots, fake accounts or legit users based on their comments, likes, posts, public data only.
I'm ...
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0
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9
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Best Practices For Dealing With This Scenario
I'm presently building a spam classifier. The model is unable to even overfit the training set at present. To investigate, I plotted the distributions of the model's features, and compared them across ...
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3
votes
1
answer
35
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Who is supposed to label my sentiment analysis? Linguistics or psychologist?
I'm starting off my undergraduate research on text classification even though I'm still considered new to this topic. I've collected more than 20K data from Twitter. I've been trying to label the data ...
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2
votes
1
answer
63
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Labeling and aggregating features issue
I am trying build a simple binary classifier (some tree based algorithm for now) and my training data will have features aggregated at the user level. So I'll have a unique records of each user. These ...
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vote
1
answer
15
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Classifying visual environment in Tensorflow CNN (video analytics)
I am given a selection of videos of users exploring simulated 3D enviroments (kind of looks like the Sims video game) and I am tasked with being able to classify each room using a tensorflow framework....
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3
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81
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How to detect outliers to lable my unsupervised data?
I have unsupervised sensor data and i want to lable each row of data as anomaly or normal. Here K-mean clustering will work?
- 171
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10
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Transformer removes heading labels [closed]
Question: Is there a way to retain/include headers once they go through a make_column_transformer?
My dataframe has the usual columns and rows, but a header is included.
Example:
When I take the data ...
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64
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Label description for scikit-learn Diabetes dataset
I am studying how to build a regression model using the Diabetes dataset from scikit-learn and I cannot find a good interpretation for the target value, meaning that I do not know what value would be ...
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vote
1
answer
137
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One hot vector output in classification task
I'm working on CNN model and I used one hot vector type of labels. The number of classes is 3: [1,0,0], [0,1,0], [0,0,1].
net(x)
I'm getting such an output: [0....
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1
answer
580
views
What is the difference between a bounding box and ROI (Region of Interest)
I was reading about the Fast RCNN for object detection. From what I understand, it uses pre-computed ROI's (using selective search) and uses these to predict the bounding box offsets and uses smooth ...
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1
vote
1
answer
54
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Which samples to inspect in a noisy labeled classification task?
I have a dataset with noisy labels on which I train a binary classifier. Inspecting the loss I see some samples were misclassified with high confidence and others were classified with indecision ...
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1
answer
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Changing order of LabelEncoder() result
Assume I have a multi-class classification task. The labels are:
Class 1
Class 2
Class 3
After LabelEncoder(), the labels are transformed into 0-1-2.
My questions are:
Do the labels have to start ...
- 175
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1
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30
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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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1
answer
50
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How would you build a big production ready image training dataset from scratch?
How would you most likely create a large production ready image training dataset from scratch including annotations for a image classification task?
We will take a large amount of images (~1 million) ...
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3
votes
2
answers
221
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Is there a clustering algorithm which accepts some clusters as input and outputs some more clusters?
Heres the task: I have data I don't know much about. The final task is to build a classifier to classify the samples into a few categories. Some of the categories are pretty clear, we can easily use ...
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1
answer
1k
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MultiLabelBinarizer() with inverse_transform()
I have multilabel labels. Elements in a label mean voting. Here is how labels look:
...
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1
answer
67
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Is there a deep learning method for 3D labels?
As the question says, I want to feed labels into a neural net that are three dimensional. Let's say that I have 3 possible labels and each one of my data points corresponds to a percentage of those ...
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3
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452
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Should you turn off label smoothing when validating?
As the subject says. On one hand, the answer should be yes because label smoothing is a regularization feature and how can you know if it improves performance without turning it off? On the other hand,...
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2
votes
2
answers
201
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How to train a machine learning algorithm with multiple labels
I have the following challenge and I very much hope that there is a solution to it. I also suspect that there is a simple approach to it. I just don't see it at the moment. Any help or advice is ...
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vote
1
answer
879
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sklearn serialize label encoder for multiple categorical columns
I have a model with several categorical features that need to be converted to numeric format. I am using a combination of LabelEncoder and OneHotEncoder to achieve this.
Once in production, I need to ...
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0
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28
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Excluding "mislabeled" examples in training set based on out of time data
This question is specifically regarding imperfect labels.
I'd like to understand the theoretical and practical implications of removing examples from the training set based on information obtained ...
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1
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67
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Get Label Statistics of Image Dataset
I have a labeled image dataset, where the images are in subfolders and there is one Pascal XML per image with the labels.
I would like to compute stats like: how many images have exactly two labels?
...
1
vote
1
answer
860
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How to fix spelling mistakes in data?
I have an input data file which contains list of drug names.
I have more than 1000 unique drug names. However, the drug names has spelling mistakes and space character issues.
For ex: we have ...
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vote
1
answer
175
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LSTM Time-series classification - derived feature
I have a time-series dataset and I want to derive a new feature based on a date column which I believe might improve my predictive model. The feature is if it's weekday or weekend.
I am not sure how ...
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vote
1
answer
234
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How to trust the labels generated using ML models?
I have a dataset of patient records. But I do not know whether he is +ve for a cancer or not. So, I do not have the labels in my dataset.
Now I can run a machine learning models like clustering to ...
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votes
1
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104
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why we need data labelling tool for computer vision?
Before start training images with tensorflow object detection api we need to use labelling tool to annotate our images and converted to XML format.
What happens when we convert our annoted image to ...
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41
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LabelEncoder with a Multi-Layer Perceptron?
So we're working on a machine learning project at work and it's the first time I'm working with an actual team on this. I got pretty good results with a model that uses the following SKLearn pipeline:
...
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1
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41
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When unsupervised learning is more beneficial in comparison with supervised learning even the labelings are existed?
When unsupervised learning is more beneficial in comparison with supervised learning even the labeling are existed?
If there is no labeling the unsupervised learning is better than supervised learning ...
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votes
2
answers
530
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Can I use confident predictions to correct incorrect labels?
From visual inspection of a sub-portion of my data, I estimate that around 5-6% of the labels are incorrect.
My classifier still performs well and when I take prediction probabilities that are above ...
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votes
1
answer
574
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How is a coincidence matrix constructed for computing Krippendorff's alpha?
I am looking at two documents to help me learn about constructing coincidence matrices in order to gain a better understanding of Krippendorff's alpha. I am using these two:
https://repository.upenn....
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votes
3
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349
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Is (nearly) all data separable?
Suppose I have some data set with two classes. I could draw a decision boundary around each data point belonging to one of these classes, and hence, separate the data, like so:
Where the red lines ...
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votes
1
answer
605
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Discriminator of a Conditional GAN with continuous labels
OK, let's say we have well-labeled images with non-discrete labels such as brightness or size or something and we want to generate images based on it. If it were done with a discrete label it could ...
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