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Questions tagged [active-learning]

28 questions
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2 answers

What is the difference between active learning and reinforcement learning?

From Wikipedia: Active learning is a special case of machine learning in which a learning algorithm can interactively query a user (or some other information source) to label new data points with the desired outputs. Reinforcement learning (RL)…
Moradnejad
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Overfitting in active learning

How can I make sure that the initial model trained on a small dataset will not suffer from overfitting before applying the active learning sampling techniques? because I will use this model to select new unlabeled samples.
user119783
5
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1 answer

What is the difference between continual learning and active learning?

As per my understanding, active learning is a kind of continual learning. Is there any difference between them?
Chandan Gautam
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Is active learning able to detect challenging cases?

Let's say we have a set of data points that need to be labelled for a classification task. In the pool-based active learning, if we go with the uncertainty measure, is the AL approach able to detect challenging cases? By challenging cases I mean…
Sarah
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Gaussian process regressor returns almost identical std for all datapoints

I am using a Gaussian process regressor as the regressor for active learning and I use its standard deviation to choose the next training inctance (the one with the highest std is chosen). However, the std values returned by the regressor are almost…
Ash
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3
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Approaches to fit a theoretical model on a physical device

Happy to join this community. Thank you in advance for your kind help! :) Intro I have a physical device characterized by its internal parameters, of which I know the nominal values. I also have the theoretical model of the device, that differs from…
FlyerDragon
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2 answers

How to construct a test set for an active learning project?

With active learning I hope to keep the annotation effort to a minimum, yet building still a good classifier. My initial starting point is that I have about 20k images which can belong to ten different classes, and have 0 labeled images at the…
ziggyler
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What is the correct way to use Active Learning on a huge and unbalanced text dataset?

I am working on a huge and unlabeled text dataset. It has over 30M lines (= sentences). We are trying to detect illegal sentences by analyzing 20 different legal issues (e.g. racism, insults, etc.). So, this is a multi-label classification problem.…
Alexandre GAREL
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Recommendation system with active learning

I have data where companies ask users to score a bunch of questions but some items may be randomly chosen while others are personalized. Users score higher in personalized questions on average. I have a user ID, question ID, corresponding score of…
lll
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2
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1 answer

Generic strategy for object detection

I have a huge collection of objects from which only a tiny fraction are in a class of interest. The collection is initially unlabelled, but labels can be added using an expensive operation (for example, by human). Currently I use the simple generic…
Valentas
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Is this approach for Active Learning correct?

Let's say that we have 10,000 unlabeled documents, and we want to use pool-based sampling with batch size of 5. And we will use least confidence (LC) for querying strategy. Is this outline of active learning reasonable: 1) Randomly select 30…
Akavall
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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 image-processing) is often a daunting task. Is there…
Pieter
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How continuous learning differs from active learning?

I have known Active Learning for a while and I am wondering what is the difference between the well known AL, and Continuous Learning? Is this a new buzzword for the old approach or is there anything new to it on top of AL?
sophros
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Self-attention model trained with active learning stops learning after a few iterations

I'm doing some active learning with uncertainty sampling on a self-attention model implemented in PyTorch. The algorithm works as follows (steps 3-7 are repeated for 14 iterations): 1. Take 10% of the data as training set, L 2. Train the model on…
razumichin
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Active learning with mixture model cluster assignments - am I injecting bias here?

Suppose I have a dataset of people's phone numbers and heights, and I'm interested in learning the parameters $p_{girl}$, $p_{boy}=1-p_{girl}$, $\mu_{boy}$, $\mu_{girl}$, and overall $\sigma$ governing the distribution of peoples' heights. I don't…
goopy
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