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  2. Perceptron - Wikipedia

    en.wikipedia.org/wiki/Perceptron

    By the perceptron convergence theorem, a perceptron would converge after making at most mistakes. If we were to write a logical program to perform the same task, each positive example shows that one of the coordinates is the right one, and each negative example shows that its complement is a positive example.

  3. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.

  4. Probably approximately correct learning - Wikipedia

    en.wikipedia.org/wiki/Probably_approximately...

    The learner must be able to learn the concept given any arbitrary approximation ratio, probability of success, or distribution of the samples. The model was later extended to treat noise (misclassified samples). An important innovation of the PAC framework is the introduction of computational complexity theory concepts to

  5. Vapnik–Chervonenkis dimension - Wikipedia

    en.wikipedia.org/wiki/Vapnik–Chervonenkis...

    is a straight line as a classification model on points in a two-dimensional plane (this is the model used by a perceptron). The line should separate positive data points from negative data points. There exist sets of 3 points that can indeed be shattered using this model (any 3 points that are not collinear can be shattered).

  6. Kernel perceptron - Wikipedia

    en.wikipedia.org/wiki/Kernel_perceptron

    Plugging these two equations into the training loop turn it into the dual perceptron algorithm. Finally, we can replace the dot product in the dual perceptron by an arbitrary kernel function, to get the effect of a feature map Φ without computing Φ(x) explicitly for any samples. Doing this yields the kernel perceptron algorithm: [4]

  7. Backpropagation - Wikipedia

    en.wikipedia.org/wiki/Backpropagation

    The LeNet was published in 1989 to recognize handwritten zip codes. In 1992, TD-Gammon achieved top human level play in backgammon. It was a reinforcement learning agent with a neural network with two layers, trained by backpropagation. [48] In 1993, Eric Wan won an international pattern recognition contest through backpropagation. [49] [50]

  8. These are the pedophile symbols you need to know to protect ...

    www.aol.com/news/2016-04-26-these-are-the...

    In March, a mother was horrified to find a pedophile symbol on a toy she bought for her daughter. Although the symbol was not intentionally placed on the toy by the company who manufactured the ...

  9. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    The quantum properties loaded within the circuit such as superposition can be preserved by creating the Taylor series of the argument computed by the perceptron itself, with suitable quantum circuits computing the powers up to a wanted approximation degree. Because of the flexibility of such quantum circuits, they can be designed in order to ...

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