Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping

W.M. Brown; T.D. Gedeon; Adrian Baddeley; D.J. Groves

Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping

W.M. Brown, T.D. Gedeon, Adrian Baddeley, D.J. Groves

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

Original language	English
Title of host publication	Not available
Publisher	International Association for Mathematical Geology
Pages	257-268
Volume	1
Publication status	Published - 2002
Event	Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping - Duration: 1 Jan 2002 → …

Conference

Conference	Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping
Period	1/01/02 → …

Cite this

@inproceedings{80e320d124784d3b9e794d773127a3fb,

title = "Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping",

author = "W.M. Brown and T.D. Gedeon and Adrian Baddeley and D.J. Groves",

year = "2002",

language = "English",

volume = "1",

pages = "257--268",

booktitle = "Not available",

publisher = "International Association for Mathematical Geology",

note = "Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping ; Conference date: 01-01-2002",

}

Brown, WM, Gedeon, TD, Baddeley, A & Groves, DJ 2002, Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping. in Not available. vol. 1, International Association for Mathematical Geology, pp. 257-268, Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping, 1/01/02.

Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping. / Brown, W.M.; Gedeon, T.D.; Baddeley, Adrian et al.
Not available. Vol. 1 International Association for Mathematical Geology, 2002. p. 257-268.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

T1 - Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping

AU - Brown, W.M.

AU - Gedeon, T.D.

AU - Baddeley, Adrian

AU - Groves, D.J.

PY - 2002

Y1 - 2002

M3 - Conference paper

VL - 1

SP - 257

EP - 268

BT - Not available

PB - International Association for Mathematical Geology

T2 - Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping

Y2 - 1 January 2002

ER -