Questions tagged [perceptron]

Perceptron is a basic linear classifier that outputs binary labels.

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Understanding computations of Perceptron and Multi-Layer Perceptrons on Geometric level

I am currently watching amazing Deep Learning lecture series from Carnegie Melllon University, but I am having little bit of trouble understanding how Perceptrons and MLP are making their decisions on ...
Stefan Radonjic's user avatar
3 votes
2 answers
641 views

Normalizing the final weights vector in the upper bound on the Perceptron's convergence

The convergence of the "simple" perceptron says that: $$k\leqslant \left ( \frac{R\left \| \bar{\theta} \right \|}{\gamma } \right )^{2}$$ where $k$ is the number of iterations (in which the weights ...
Qwerto's user avatar
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2 answers
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Strange behavior with Adam optimizer when training for too long

I'm trying to train a single perceptron (1000 input units, 1 output, no hidden layers) on 64 randomly generated data points. I'm using Pytorch using the Adam optimizer: ...
Bai Li's user avatar
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3 votes
1 answer
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Learning rate in the Perceptron Proof and Convergence

Every perceptron convergence proof i've looked at implicitly uses a learning rate = 1. However, the book I'm using ("Machine learning with Python") suggests to use a small learning rate for ...
Qwerto's user avatar
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0 votes
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How is calculated the error with multiple output neurons in neural network?

Machine Learning books generally explains that the error calculated for a given sample $i$ is: $e_i = y_i - \hat{y_i}$ Where $\hat{y}$ is the target output and $y$ is the actual output given by the ...
heresthebuzz's user avatar