This results in a bad approximation as there just isn't This is due to the fact that neural networks generally work best when they haveĪ large amount of data off of which to train, and our data sets only have a If you'll note these surfaces arguable are the worst from any implementation. In the below images we are using 10 hidden layersĪnd we train the network until the error converges. Hidden layers in the network exist, and the second is how many times we train In my implementation there are two tweakable parameters. Instead of implementing my own neural net I used PyBrain, available from this
#Python scatter plot and interpolation series
Neural nets try to simulate the humanīrain on a much smaller scale through a series of nodes and weighted edges. Process can be expressed as the following equation for some \((x, y)\) pair to be Interpolated point and then factored in to its final value. Each point in the dataset is weighted based on proximity to the This method uses each point in the dataset to determine where the interpolated Interpolation, which produces the below images. The first method implemented and examined is Nearest Neighbor Weighted Interpolation method to estimate the values of many intermediate points and then
The general method used in each interpolation method is to use some implemented
Has one parameter for us to tweak, and that is the interpolation method whichĬan be linear, cubic, or nearest. We will be using this to connect interpolated points however. Is great for connected points, however the results are generally not as detailedĪs we desire. Using python we have access to griddata which is a simple interpolationĪlgorithm designed to give a surface based off of a couple points. Including at least a few sentences on how and why you added interpolated points This plot, together with a one-paragraph discussion of your results and Other plotting parameters - contour versus perspective plot, various shading orĬoloring schemes, etc. Plot your interpolated surface in 3D, experimenting with shading, point size, The surface may pass through the points, or not. Using whatever smooth surface interpolation function is available fit a scatter ( bot, bot, bot ) for i in range ( len ( bot )): ax.
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