In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function.

What is density estimation in data science?

Density estimation is estimating the probability density function of the population from the sample. This post examines and compares a number of approaches to density estimation. By Ajit Samudrala, Data Scientist at Symantec. Statistics revolve around making estimations about the population from a sample.

What is density estimation problem?

Density estimation is the problem of reconstructing the probability density function using a set of given data points. Namely, we observe X1, ··· ,Xn and we want to recover the underlying probability density function generating our dataset. A classical approach of density estimation is the histogram.