Correction in the formula for mean squared error #845
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norvig
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Mar 14, 2018
neural_nets.ipynb
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| "In both the Perceptron and the Neural Network, we are using the Backpropagation algorithm to train our weights. Basically it achieves that by propagating the errors from our last layer into our first layer, this is why it is called Backpropagation. In order to use Backpropagation, we need a cost function. This function is responsible for indicating how good our neural network is for a given example. One common cost function is the *Mean Squared Error* (MSE). This cost function has the following format:\n", | ||
| "\n", | ||
| "$$MSE=\\frac{1}{2} \\sum_{i=1}^{n}(y - \\hat{y})^{2}$$\n", | ||
| "$$MSE=\\frac{1}{2n} \\sum_{i=1}^{n}(y - \\hat{y})^{2}$$\n", |
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Oops, there are conflicts agin, due to another PR. These are really hard to review for .ipynb |
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Should I send another PR after pulling the latest changes from the repository? @norvig |
Changes from original repo
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This PR contains duplicated changes. It will be easier if you close this PR, update your working directory, create a new branch and open a fresh pull request. Be sure to make a branch before you commit changes. The master branch is for updating the local directory from the upstream repo. |
Bringing up to date with original repo
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There was a minor error in the formula for mean squared error in neural_nets.ipynb