#Scipy optimize minimize example how to

If the activation function are in the same family of original model, the estimation is often very good. The last model is a polynomial with optional degree.Р”Р„ll the above functions need some activation functions. Therefore, there are 7 parameters which four of them are weights and three of them are biases. The second one is a perceptron with three nodes the input has two node and output is a single node. The first one is an activation function after a linear transformation. Then, three non-linear models where proposed. For example function x*sinc(2*pi*f*x) is a very non-linear function, specially when the frequency of sinc increases. Then, step by step the non-linearity of function will be increased.

The JupyterLab notebook is accessible in GitHub.Р”Р‡irst, a non-linear function is made for producing the training data.

Here we will use several Scipy tools to get more familiar with them.

#Scipy optimize minimize example how to

РІР‚Сњ How to make a good regression model for a function with complex shape? РІР‚СљР”Р„s it was discussed in this post, it is possible to view this problem from several aspect. The important question that this experiment wants to answer it is: The experiments have been done in a single JupyterLab notebook and run on a 12 CPU core server node. Also, these are my idea and other researchers may get better results from this library with tunnings. Here, I will not introduce all available functions, but just some of them which seems more famous. But in applications with tenth or hundredth parameters, it is not possible to use this library because it runs very slow and also function definition would be too hard. Based on my observation, when the number of independent variables are few, these methods work fine. Scipy, a very well-known Python library, have some fundamental but powerful tools for optimization.