Questions tagged [supervised-learning]

For questions related to supervised learning.

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1answer
102 views

What needs to be done to make a fair algorithm?

What needs to be done to make a fair algorithm (supervised and unsupervised)? In this context, there is no consensus on the definition of fairness, so you can use the definition you find most ...
3
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2answers
535 views

What is the difference between reinforcement learning and AutoML?

My vague understanding of reinforcement learning (RL) is that it's very similar to supervised learning except that it updates on a continuous feed of data/activity, this to me sounds very similar to ...
1
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0answers
39 views

How can I generate keywords associated with a website given its URL?

I have a column with links to websites and another column with keywords from those websites. I have to find a map between these two, such that for a new input, which is a website's URL, I can generate ...
1
vote
1answer
130 views

Class imbalance and “all zeros” one-hot encoding?

I tried this example for a multi class classifier, but when looking at the data I realized two things: There are many examples of "all zeros" vectors, that is, messages that don't belong in any ...
2
votes
1answer
75 views

What are the most common methods to enable neural networks to adapt to changing environments?

For real applications, concept drifts often exist, i.e., the relationship between the input and output changes overtime. Thus, we need our AI or machine learning system to quickly adapt to the ...
5
votes
2answers
97 views

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 $[...
3
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1answer
725 views

Are the training loss and validation loss plotted per sample or per batch?

I am using a CNN to train on some data, where training size = 21700 samples, and test size is 653 samples, and say I am using a batch_size of 500 (I am accounting for samples out of batch size as well)...
3
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0answers
113 views

What are the differences between CRF and HMM?

What I know about CRF is that they are discriminative models, while HMM are generative models, but, in the inference method, both use the same algorithm, that is, the Viterbi algorithm, and forward ...
4
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2answers
108 views

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. ...
1
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1answer
390 views

Does neuroevolution require a labelled dataset?

A neuroevolution algorithm, such as DXNN, can be used to refine the topology and weights of an artificial neural network (ANN). The GA will require a fitness function, which means you need labeled ...
7
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1answer
459 views

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-...
3
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1answer
136 views

Why are neural networks always trained “by themselves”?

In the current rush of artificial intelligence research, fueled by NN, independent of the paper I choose, the NN are always trained by themselves. Sure, there are architectures that combine CNN and ...
2
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4answers
128 views

How is regression machine learning?

In regression, in order to minimize an error function, a functional form of hypothesis $h$ must be decided upon, and it must be assumed (as far as I'm concerned) that $f$, the true mapping of instance ...
3
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1answer
162 views

How Does AlphaGo Zero Implement Reinforcement Learning?

AlphaGo Zero (https://deepmind.com/blog/alphago-zero-learning-scratch/) has several key components that contribute to it's success: A Monte Carlo Tree Search Algorithm that allows it to better search ...
5
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1answer
869 views

Variational Autoencoder task for better feature extraction

I have a CNN with the regression task of a single scalar. I was wondering if an additional task of reconstructing the image (used for learning visual concepts), seen in a DeepMind presentation with ...
1
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1answer
677 views

Why isn't the reverse KL divergence commonly used in supervised learning?

Forward KL Divergence (also known as cross entropy loss) is a standard loss function in supervised learning problems. I understand why it is so: matching a known a trained distribution to a known ...
2
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0answers
143 views

When to use which metric in machine learning?

In machine learning, there are several metrics to assess the quality of the models: accuracy, precision, recall, f measure, ROC (AUC), etc. There are cases when certain metrics are more appropriate ...
3
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0answers
22 views

Backpropagation: how to take into account different samples quality

I have a NN I'd like to train using supervised learning. Some samples of the training set, however, have better "quality" than others, so I'd like the algorithm to pay "special attention" to them. As ...
1
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0answers
35 views

identifying pattern in datasets

i am new to machine learning. i'm trying to identify driving pattern through accelerometer and gyroscope sensor. i have been collecting the data of both the sensors and have been storing them in .csv ...

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