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Group Assignment and Annual Average Daily Traffic Estimation of Short-term Traffic Counts Using Gaussian Mixture Modeling and Neural Network Models
(2016-09-13)
The grouping of similar traffic patterns and cluster assignment process represent the most critical steps in AADT estimation from short-term traffic counts. Incorrect grouping and assignment often become a significant ...
ApproxML: Efficient Approximate Ad-Hoc ML Models Through Materialization and Reuse
(2019-12-10)
Machine Learning (ML) has become an essential tool in answering complex predictive analytic queries. Model building for large scale datasets is one of the most time-consuming parts of the data science pipeline. Often data ...
A supervised approach for training Gaussian Mixture Model classifiers
(2017-08-22)
A new method for training Gaussian Mixture Model (GMM) classifiers is presented. First, an objective function is defined in terms of the number of clusters, K, per class, the mean vectors, the inverse covariance matrices ...