DensityEstimation.md (691B)
1 # Density Estimation 2 3 Stats D3 4 5 **Definition:** Density estimation is the process of modeling the probability of given values for a dataset. 6 7 This can be thought of similar to a histogram without the bins. A common form of this is a kde. The reason these can be better is that it does not have binning which can make data appear innacurately depending on the cut points and bin widths. 8 9 In a general sense, kdes work by creating gaussian distributions about datapoints and then summing up these values at each point and then graphing that. This averages out the data to give a general graph of the data. The width of these gaussian distributions is dictated by the bandwidth hyperparameter.