Questions tagged [labeling]

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Chicken and egg problem in machine learning [closed]

Recently, I went through an ICLR paper SELF-LABELLING VIA SIMULTANEOUS CLUSTERING AND REPRESENTATION LEARNING. In the paper, authors discussed simultaneously labeling the images and training a network ...
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Rule based label - For attrition risk

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 votes
1 answer
75 views

Logistic Regression applied to biased dataset

I have collected a binary classification dataset in a somewhat biased way: I have thousands of unlabeled samples. A small percentage of these samples belong to the positive class. I know for a fact ...
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binary classification with labels of varying quality

I have a binary classification problem, where half my development data is labeled by a reliable source, and the other half by a less reliable one. Note that each instance gets a label from only one of ...
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1 vote
1 answer
23 views

Estimate sample size from a variable population

Context: I want to measure accuracy, precision, and recall for individual raters. Each rater completes a variable amount of labels, for ex. rater A may complete 500 in a given time period while rater ...
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1 answer
39 views

Use Naive Bayes to label unlabeled data

I have an Excel file that includes all product information (web scraped from Zalando) of 10k dresses. So for each dress/line I have multiple features available (brand, color, neckline, length...) I ...
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Labeling unlabeled data (expectation maximization)

Say I have a database (Excel) consisting of 10k different dresses and accompanying attributes (column names) for each dress (sleeve length, color, pattern, ...). I would like to label each of these ...
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Why do we multiply class labels y with linear function (w^t . x + b) in SVM or Logistic regression?

In SVM or Logistic Regression, If we want to see whether a point is properly classified or not in such case we multiply label with linear model which is, $$ y * (w^{t} * x + b) < 1 $$ For point x ...
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How to do sentiment analysis in financial news?

I already have financial news that I got from financial news sites. Now I want to apply sentiment analysis to classify news as positive, neutral, or negative. I do not know what to do. I know some ...
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1 answer
29 views

How to combine two manual classifications

We are manually classifying texts as positive (+1), neutral (0) or negative (-1). The purpose is to train a sentiment analysis classifier. We are two people, and we have both classified the same ...
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1 vote
1 answer
38 views

Question on labels in machine-learning

Suppose that $X$ and $T$ are both random variables. Where $T$ is a label. I just want to ask is tha finding probabilities on the label $P(T=t)$ or conditional probabilities $P(X=x|T=t)$ meaningful or ...
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Correct or most common term for altering a loss function to ignore unlabelled pixels?

In my experience it is quite commonplace to alter the loss function used when training a neural network for segmentation to ignore the contribution to the loss of unlabelled pixels. There are a few ...
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label encode date [closed]

I am working in R. I want to set initial date(6-2018) as 0 and last date as(12-2020) whatever the last value is. I have around 19 unique dates. I tried to Label encode them but it changes to 0,1,1,1,1,...
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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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Comparing quality of automatically labeled data

I have two algorithms for automatically labeling data for a computer vision task. The dataset is large, and it's not feasible to inspect visually. Can I determine which labeling is higher quality ...
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2 votes
1 answer
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How to make a decision - when there is a tie and no human expert

We have two algorithms (simple rule-based) working on labeling the dataset as "Yes" and "No" for a disease. There is no ML involved in this task. For ex: If Algo 1 says subject 1 ...
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For binary classification learning problems, how should I label instances where I'm only 60% sure?

I've come across a few binary classification problems lately where the labelling was challenging even for an expert. I'm wondering what I should do with this. Here are some of my suggestions to get ...
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Label-encoding nominal variables

I am aware of the practice that label encoding is preferred for ordinal variables while ...
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How to formulate a machine learning problem?

Virtually no books talk about how to formulate a ML problem, especially the process of creating the right label. Here I use an online hotel search portal as an example to explain my thought process ...
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Conflict vs Overlap in Snorkel Label Analyzer

I am currently working on a weakly supervised approach to labeling training data. Snorkel helps make the process a lot easier by providing methods to facilitate labeling, modeling, etc. Snorkel ...
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1 vote
1 answer
14 views

Principled Method for Reweighting Labels Based on Labeler Consistency?

I have a large dataset where each datum has been labeled by multiple raters, and each rater has labeled multiple datums. Rather than assigning to each datum the naive average of all of the labels ...
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1 vote
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mislabeled data Event Detection, neural language processing

I'm doing some experiment with sequence labeling problems, more specifically is Event detection problem. But I'm encountering with the mislabeled data issue. In my dataset, there are many tokens that ...
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1 vote
1 answer
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Active learning with a unlabelled pool - standard references & model-based labelling of the pool?

I'm looking into active learning for a multi-class classification problem, where there is a large pool of unlabelled data. I start out with a small set of labelled data and can labelled some more of ...
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5 votes
6 answers
4k views

How to deal with incorrect labels in classification?

I have a dataset with 2 classes: A and B. The problem is that 20% to 30% of the samples of class B are mislabeled (labeled as B but the right label is A) and I am not able to identify those mistakes. ...
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1 vote
2 answers
355 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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1 answer
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Does mislabeling due to adversarial noise in features count as adversarial machine learning?

According to the traditional definition, Adversarial machine learning is a technique employed in the field of machine learning which attempts to fool models through malicious input. However, I have ...
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186 views

Using label encoder on a categorical feature that we want to embed

I have a dataset with feature that have very high cardinality, doing one-hot encoding is not an option because of memory limitations, so I am currently label encoding this feature and then I feed that ...
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0 votes
2 answers
128 views

Directly using Inaccurate Labels vs. Transfer Learning

I have a two ML models model_a and model_b that optimize on an event, label_a. I have a small volume of labels for model_a and a large volume of labels for model_b. The features used in these models ...
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1 vote
0 answers
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How to you label (caption) the table title? (for example:Tests of Between-Subjects Effects for One-way ANOVA)

How do you lable/caption a table under One-way ANOVA? Tests of Between-Subjects Effects for One-way ANOVA OR ...
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1 vote
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Binary least squares classification labeling {0,1} vs {1,-1) [closed]

I am trying to find the best possible line which discriminates my data with least squares. I have 2 points, $\pmb{x}_0=\{1,2\}$ which belongs to the class $y=+1$ and $\pmb{x}_1=\{2,1\}$ which belongs ...
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5 votes
1 answer
3k views

Do ordinal variables require one hot encoding?

For categorical variables, one hot encoding is a must if the variable is non-binary . But what about ordinals? These variables are ordered but are mutually exclusive. Do they require the same ...
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1 answer
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Labels in Out-of-time validation

I have a binary classification problem and I use out-of-time validation to validate my models. My question is regarding the label. There is a lag in identifying the correct label. Simplified example: ...
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3 votes
1 answer
99 views

Elastic net/LASSO with soft labels

Sometimes you do not have firm Y/N labels, but e.g. 80% probability of Y as a label. E.g. this happens, if you train a model on a small amount of labelled data, predict for a large amount of ...
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0 votes
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Meaning of sparse annotation for images?

what is sparse annotation? Is it pixel-wise labeling for images. what are the other types of annotation?
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3 votes
2 answers
83 views

is it scientifically correct to label data by model built using golden data?

I am trying to find a labeled dataset for users profiles pictures with their personality traits scores. Unfortunately, I did not find any and therefore, I decided to crawl twitter for public users ...
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0 votes
2 answers
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When is it okay to label data yourself? (And semi-supervised learning)

i'm pretty new to machine learning so i think this might be a realy basic question. Let's imagine the following scenario: I want to classify projects as either active or inactive. Projects can be ...
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4 votes
2 answers
258 views

Regression algorithm on [0,1] with lots of mislabeled data

I have a training set mapping some Likert-scale variables (integers between 1 and 7, rescaled to real numbers between 0 and 1) to predict a continuous variable between 0 and 1. The data set is ...
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1 vote
0 answers
67 views

How to train NN if training data has skewed distribution?

I would like (to try) to train a NN to predict the outcome, given the initial condition. For simplicity lets assume there are 100 input parameters which can cause either OutcomeA or OutcomeB. Because ...
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1 vote
2 answers
49 views

The correct title for y axis

My question is rather simple but it seems that statisticians have different views about it.. If a bar chart shows the percentage of children under 5 that had fever in the past 2 weeks by country.. ...
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0 votes
1 answer
30 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 ...
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1 vote
1 answer
538 views

What do I label the legend in this regression plot

What do I label the predicted values, or fitted model in this chart? (In the legend) Fitted model? Fit model? Predicted? Regression? What are my options? The black line and points are the actual ...
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0 votes
1 answer
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How should I sample data from my dataset to be manually labeled for a SVM?

Assume I have a $2$-dimensional dataset $X=(x_1, x_2)$ where both features are not uniformly distributed over their respective ranges. I now need to select $100$ datapoints from this dataset to be ...
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3 votes
1 answer
272 views

Logistic regression - labeling outcome by confidence of classification [closed]

We have trained our logistic regression model to classify candidates attending interviews as 'pursue' or 'fail' (two possible outcome) Now as a post prediction step, we are planning to categorise ...
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0 votes
1 answer
40 views

Catch more information in neighbouring the 1 and -1 labels

I have labels I feed to a LSTM model. I noticed that there were to few 1s and -1s compared to the number of 0s. I have at least 99.9% of 0s and the rest are 1s and -1s. I considered using weighted ...
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1 vote
0 answers
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Best labelled dataset for training a binary image classifier

I want to train some binary classifiers in Keras (e.g. to decide if there is person on a picture or if there is a vehicle on it). What is the best dataset to use for this? I mean datasets like these. ...
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13 votes
2 answers
8k views

Do more object classes increase or decrease the accuracy of object detection

Assume you have an object detection dataset (e.g, MS COCO or Pascal VOC) with N images where k object classes have been labeled. You train a neural network (e.g., Faster-RCNN or YOLO) and measure the ...
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4 votes
0 answers
625 views

Medium Frequency Trading - Better labelling strategy?

The mid-price at time $t$ is denoted by $$p_t = \frac{s_t^{a,1} + s_t^{b,1}}{2}.$$ This mid-price can evolve in minimum increments of half a tick but is almost always observed to move at ...
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  • 101
0 votes
1 answer
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Strategy to label stock prices

Suppose I have the prices of an action XXXX at the second for three years. I want to use the data to train my Deep Neural Network model for standard day trading purposes (i.e. High Frequency Trading). ...
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0 votes
1 answer
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How to give user defined labels to data extracted from web

I have built a web scraper to extract data from a site so that it can later be translated/transliterated. I traversed every branch of the HTML tree to extract every string and its raw path along with ...
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2 votes
1 answer
1k views

Supervised learning: setting labels on sliding windows of sensor data

Suppose that I have a set of accelerometer data collected with one sensor and one label for each measured data point. These labels describe different states of my system e.g., $state_A, state_B, ...
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