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clarify definition of error.

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lessons/3-NeuralNetworks/03-Perceptron/README.md
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@ -29,7 +29,7 @@ where f is a step activation function
## Training the Perceptron
To train a perceptron we need to find a weights vector w that classifies most of the values correctly, i.e. results in the smallest **error**. This error is defined by **perceptron criterion** in the following manner:
To train a perceptron we need to find a weights vector w that classifies most of the values correctly, i.e. results in the smallest **error**. This error E is defined by **perceptron criterion** in the following manner:
E(w) = -&sum;w<sup>T</sup>x<sub>i</sub>t<sub>i</sub>