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The "MultiLayerPerceptron" page has been changed by YexiJiang: http://wiki.apache.org/hama/MultiLayerPerceptron?action=diff&rev1=12&rev2=13 A [[http://en.wikipedia.org/wiki/Multilayer_perceptron|multilayer perceptron]] is a kind of feed forward [[http://en.wikipedia.org/wiki/Artificial_neural_network|artificial neural network]], which is a mathematic model inspired by the biological neural network. The multilayer perceptron can be used for various machine learning tasks such as classification and regression. - Here is an example multilayer perceptron: + The basic component of a multilayer perceptron is the neuron. + In a multilayer perceptron, the neurons are aligned in layers and in any two adjacent layers the neurons are connected in pairs with weighted edges. + A practical multilayer perceptron consists of at least three layers of neurons, including one input layer, one or more hidden layers, and one output layers. + + Here is an example multilayer perceptron with 1 input layer, 1 hidden layer and 1 output layer: {{https://docs.google.com/drawings/d/1DCsL5UiT6eqglZDaVS1Ur0uqQyNiXbZDAbDWtiSPWX8/pub?w=813&h=368}} + - The basic component of a multilayer perceptron is the neuron. - A typical multilayer perceptron consists of at least two layers of neurons, including one input layer, zero or more hidden layers, and one output layers. == How Multilayer Perceptron works? == To be added...
