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diff --git a/docs/ml-ann.md b/docs/ml-ann.md deleted file mode 100644 index 6e763e8f41..0000000000 --- a/docs/ml-ann.md +++ /dev/null @@ -1,62 +0,0 @@ ---- -layout: global -title: Multilayer perceptron classifier - ML -displayTitle: <a href="ml-guide.html">ML</a> - Multilayer perceptron classifier ---- - - -`\[ -\newcommand{\R}{\mathbb{R}} -\newcommand{\E}{\mathbb{E}} -\newcommand{\x}{\mathbf{x}} -\newcommand{\y}{\mathbf{y}} -\newcommand{\wv}{\mathbf{w}} -\newcommand{\av}{\mathbf{\alpha}} -\newcommand{\bv}{\mathbf{b}} -\newcommand{\N}{\mathbb{N}} -\newcommand{\id}{\mathbf{I}} -\newcommand{\ind}{\mathbf{1}} -\newcommand{\0}{\mathbf{0}} -\newcommand{\unit}{\mathbf{e}} -\newcommand{\one}{\mathbf{1}} -\newcommand{\zero}{\mathbf{0}} -\]` - - -Multilayer perceptron classifier (MLPC) is a classifier based on the [feedforward artificial neural network](https://en.wikipedia.org/wiki/Feedforward_neural_network). -MLPC consists of multiple layers of nodes. -Each layer is fully connected to the next layer in the network. Nodes in the input layer represent the input data. All other nodes maps inputs to the outputs -by performing linear combination of the inputs with the node's weights `$\wv$` and bias `$\bv$` and applying an activation function. -It can be written in matrix form for MLPC with `$K+1$` layers as follows: -`\[ -\mathrm{y}(\x) = \mathrm{f_K}(...\mathrm{f_2}(\wv_2^T\mathrm{f_1}(\wv_1^T \x+b_1)+b_2)...+b_K) -\]` -Nodes in intermediate layers use sigmoid (logistic) function: -`\[ -\mathrm{f}(z_i) = \frac{1}{1 + e^{-z_i}} -\]` -Nodes in the output layer use softmax function: -`\[ -\mathrm{f}(z_i) = \frac{e^{z_i}}{\sum_{k=1}^N e^{z_k}} -\]` -The number of nodes `$N$` in the output layer corresponds to the number of classes. - -MLPC employes backpropagation for learning the model. We use logistic loss function for optimization and L-BFGS as optimization routine. - -**Examples** - -<div class="codetabs"> - -<div data-lang="scala" markdown="1"> -{% include_example scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala %} -</div> - -<div data-lang="java" markdown="1"> -{% include_example java/org/apache/spark/examples/ml/JavaMultilayerPerceptronClassifierExample.java %} -</div> - -<div data-lang="python" markdown="1"> -{% include_example python/ml/multilayer_perceptron_classification.py %} -</div> - -</div> |