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.

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13 views

Relation between number of landmark points and learning accuracy

Is there any relation between number of landmark points on an image and the accuracy of learning these landmarks? For example for detecting nose tip and eye corners, can we say that adding some labels ...
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0answers
7 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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26 views

Which samples to inspect?

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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1answer
20 views

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 ...
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24 views

How do I identify the postulated 600 object classes in OpenImages v. 6?

I have downloaded the OpenImages version 6 image sets (train, validation, test) from CVD Foundation as per instructions from the OpenImages homepage. The OpenImages homepage states that there are 600 ...
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1answer
14 views

(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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1answer
31 views

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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2answers
102 views

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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1answer
330 views

MultiLabelBinarizer() with inverse_transform()

I have multilabel labels. Elements in a label mean voting. Here is how labels look: ...
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1answer
25 views

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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3answers
125 views

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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1answer
66 views

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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1answer
194 views

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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20 views

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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1answer
18 views

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? ...
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1answer
106 views

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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1answer
70 views

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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1answer
207 views

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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1answer
33 views

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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1answer
25 views

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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1answer
35 views

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 ...
6
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1answer
261 views

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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1answer
253 views

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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3answers
190 views

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 ...
2
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1answer
249 views

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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1answer
17 views

Tools suitable for semi-automatic video labeling?

So far I have been using labelme to label objects in videos I use for training, but it is quite time consuming. Are there good tools to help with that? I was thinking about a tool where I label ...
2
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1answer
163 views

How to correct mislabeled data in dataset?

I have a dataset of about 300k records. Classes are highly imbalanced (which means that one may have 30k records, and the other may have only 100). Unfortunately, about 5% of records is incorrectly ...
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0answers
22 views

Create labels or annotation from two color images

I have two categories of images to use in my deep learning model. The firs category is aerial images that contain roads (such as road-1.jpg). The second category is two color images that contains road ...
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0answers
371 views

Is there a way to use Plotly as an annotation tool, for labelling time-series for instance?

I have been tasked to create a tool aimed at labelling sections and/or precise data points of a biomedical time-series. Our main framework is written in Python. I would like to know whether it is ...
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1answer
62 views

CNN for checking existance of single label

i am just thinking about training a neural network which uses data of only one single label. For example: Assuming i have many images which contain a dog. Now i want to teach the network how a dog ...
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2answers
2k views

Tool for labeling audio

I have few thousand audio signals to label into 2 different classes and save them to numpy array for further training of models. MATLAB recently released ...
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2answers
958 views

How label smoothing and label flipping increases the performance of a machine learning model

I have seen posts and research papers mentioning these techniques for improving the performance of a machine learning model. These techniques certainly make some sense in the case when we are not ...
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1answer
25 views

Quickest way of multi-labelling images?

I want to make a new dataset containg thousands of (different-sized) images. Now I need to assign multiple labels to each image. Of course I already looked at github etc. and there are good labelling ...
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1answer
9 views

Key pixels, key “features” detection in CNNs

I am working on a dataset but I don't know what the labels mean. I was wondering if using CNNs there was a way to understand which pixels where most significant for the network. A little bit in the ...
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0answers
52 views

Proportion of positive/negative label in Supervised Learning

I'm working on a Supervised Machine Learning problem and I have a question about the proportion of positive/negative label. I would like to categorize some batch as OK or NOK. But actually my batchs ...
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2answers
288 views

How to get labels in face recognition in Keras

I am building a facial recognition system. The model is complete but I am having minor issues during prediction. I used the Image data generator to load images from train and test folders and trained ...
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1answer
975 views

Clustering of multi-label data

The dataset consists of 1) a set of objects and 2) a set of labels, which are used to describe the objects. For the moment, for simplicity sake, each label can be marked as either true or false (...
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1answer
1k views

Automatic labelling of text data based on predefined entities

I'm new to NLP. I have a folder containing .txt files which are legal and specific documents. I want to label all these files based on four predefined labels. How can I do that automatically?
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1answer
1k views

How to label overlapping objects for deep learning model training

I am training yolov3 to detect a custom object (chickens). In a lot of my training images I have overlapping chickens (can only see a partial chicken etc). Is there a common practice for how to label ...
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0answers
26 views

How to label smart meter/plug data (time series)? [closed]

I would like to label smart plug data recorded in different household appliances so that I can train a machine to recognize for example when the oven is turned on. I am new to this topic and I am ...
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0answers
143 views

Transform a multiclass dataset into a multi-label one

I have a dataset of feature/label pairs. My labels are probabilities of each feature vector to belong to the K classes. Here is an example for K = 3: ...
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1answer
78 views

Suggestions for labeling data for named entity recognition [closed]

Is it good to label the data based on sub category than parent category? For example: for drugs data ... label the drugs dose as drug_dose or label the drug dose as different type of dose like ...
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1answer
126 views

Should we have only binary labels for LSTM?

Is it possible to have non-binary labels for LSTM? I mean an array like [ 100 120 140 20 50 70] Instead of [1 0 1 0 0 1 1] ...
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0answers
30 views

Correct approach to usage of class labels in cell imaging data

As part of a group project at university, we are given a series of videos of cell cultures over a 24 hour period. A number of these cells (the "knockout" cells) have had a particular gene removed, ...
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0answers
23 views

Online service for crowdsource text labbling [closed]

I'm trying to make a text classificator for short texts. For that task, I need a labeled samples dataset. I already have samples but most of them are not labeled. I'm tired to label them in excel ...
8
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1answer
585 views

How to handle preprocessing (StandardScaler, LabelEncoder) when using data generator to train?

So, I have a dataset that is too big to load into memory all at once. Therefore I want to use a generator to load batches of data to train on. In this scenario, how do I go about performing scaling ...
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1answer
86 views

Difference in labelling and normalizing train/test data

I am working on a dataset comprised of almost 17000 data points. Since it's a financial dataset and the components are many different companies, I need necessarily to split it by date. Therefore, ...
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0answers
158 views

Label construction for predictive maintenance

I am trying to do a binary classification related to predictive maintenance. The question I address is "What is the probability that the asset will fail in the next X units of time?" There is a guide ...
2
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3answers
139 views

Is there any tool for data visualization and manipulation?

I have a time series data set that I need to manually label them for supervised learning. What I am doing now is using excel to plot, and when I see the pattern that I want, I hover over the data on ...
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0answers
48 views

Merge one label with one information for classification problem or multi-label classification

I want to build a model to support decision making in order to propose or not loan insurance to clients. Because sometimes clients asking loan and loan insurance have less chance to have their loan ...