Mapping geochemical anomalies related to Fe–polymetallic mineralization using the maximum margin metric learning method

Volume: 107, Pages: 258 - 265
Published: Apr 1, 2019
Abstract
Geochemical anomaly identification is an important task in mineral exploration targeting. This task can be regarded as a binary classification problem whereby the aim is to discriminate between anomalous and not anomalous (i.e., background). We can analyze geochemical data from the aspects of frequency distributions, correlations and variances, geometrical properties of geochemical anomalies, and scale independence of geochemical patterns. In...
Paper Details
Title
Mapping geochemical anomalies related to Fe–polymetallic mineralization using the maximum margin metric learning method
Published Date
Apr 1, 2019
Volume
107
Pages
258 - 265
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