Direct Log-Density Gradient Estimation with Gaussian Mixture Models and Its Application to Clustering
Direct Log-Density Gradient Estimation with Gaussian Mixture Models and Its Application to Clustering
Estimation of the gradient of the logarithm of a probability density function is a versatile tool in statistical data analysis. A recent method for model-seeking clustering called the least-squares log-density gradient clustering (LSLDGC) [Sasaki et al., 2014] employs a sophisticated gradient estimator, which directly estimates the log-density gradients without going …