Kernel Regression
Kernel regression estimates the continuous dependent variable from a limited set of data points by convolving the data points' locations with a kernel function - approximately speaking, the kernel function specifies how to "blur" the influence of the data points so that their values can be used to predict the value for nearby locations.
Read more about this topic: Nonparametric Regression
Famous quotes containing the word kernel:
“After night’s thunder far away had rolled
The fiery day had a kernel sweet of cold”
—Edward Thomas (1878–1917)