Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [supervised-learning]

For questions related to supervised learning.

Supervised learning is a machine learning technique where a function which maps inputs to outputs is learned using a labelled training dataset. A good learned function should be able to generalise to unseen (during the training phase) data.

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What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
nbro
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What is the relation between semi-supervised and self-supervised visual representation learning?

What's the differences between semi-supervised learning and self-supervised visual representation learning, and how they are connected?
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Can autoencoders be used for supervised learning?

Can autoencoders be used for supervised learning without adding an output layer? Can we simply feed it with a concatenated input-output vector for training, and reconstruct the output part from the input part when doing inference? The output part…
rcpinto
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What are the different approaches used in Machine Learning?

There seem to be so many sub-fields, so I'm interested in getting a better understanding of the approaches. I'm looking for information on a single framework per answer, in order to allow for granularity without the overall answer getting too long.…
kakaz
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Do GANs come under supervised learning or unsupervised learning?

Do GANs come under supervised learning or unsupervised learning? My guess is that they come under supervised learning, as we have labeled dataset of images, but I am not sure as there might be other aspects in GANs which might come into play in the…
codecracker
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Can supervised learning be recast as reinforcement learning problem?

Let's assume that there is a sequence of pairs $(x_i, y_i), (x_{i+1}, y_{i+1}), \dots$ of observations and corresponding labels. Let's also assume that the $x$ is considered as independent variable and $y$ is considered as the variable that depends…
TomR
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Does AlphaZero use Q-Learning?

I was reading the AlphaZero paper Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm, and it seems they don't mention Q-Learning anywhere. So does AZ use Q-Learning on the results of self-play or just a Supervised…
Avetik
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What is the difference between imitation learning and classification done by experts?

In short, imitation learning means learning from the experts. Suppose I have a dataset with labels based on the actions of experts. I use a simple binary classifier algorithm to assess whether it is good expert action or bad expert action. How is…
user781486
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Is it possible to guide a reinforcement learning algorithm?

I have just started to study reinforcement learning and, as far as I understand, existing algorithms search for the optimal solution/policy, but do not allow the possibility for the programmer to suggest a way to find the solution (to guide their…
Cristian M
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How could decision tree learning algorithms cope with imbalanced classes?

Decision trees and random forests may or not be more suited to solve supervised learning problems with imbalanced labels (or classes) in datasets. For example, see the article Using Random Forest to Learn Imbalanced Data, this Stats SE question and…
jennifer ruurs
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What should the range of the output layer be when performing classification?

I am working on a MLP neural networks, using supervised learning (2 classes and multi-class classification problems). For the hidden layers, I am using $\tanh$ (which produces an output in the range $[-1, 1]$) and for the output layer a softmax…
LVoltz
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What is the meaning of "exploration" in reinforcement and supervised learning?

While exploration is an integral part of reinforcement learning (RL), it does not pertain to supervised learning (SL) since the latter is already provided with the data set from the start. That said, can't hyperparameter optimization (HO) in SL be…
Tfovid
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How can reinforcement learning be unsupervised learning if it uses deep learning?

I was watching a video in my online course where I'm learning about A.I. I am a very beginner in it. At one point in the course, the instructor says that reinforcement learning (RL) needs a deep learning model (NN) to perform an action. But for…
Lucas Vital
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If the accuracy of my current model is low ($50 \%$) and we want to minimize time in collecting more data, should we try other models?

Suppose we have a data set with $4,000$ labeled examples. The outcome variable is trinary (three possible categorical values). Suppose the accuracy of a given model is "bad" (e.g. less than $50 \%$). Question. Should you try different traditional…
naturalguy_12
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How can AI be used to design UI Interfaces?

I'm very new to AI. I read somewhere that AI can be used to create GUI UI/UX design. That has fascinated me for a long time. But, since I'm very new here, I don't have any idea how it can happen. The usual steps to create the UI Design…
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