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Performance evaluation and hyperparameter tuning of statistical and
  machine-learning models using spatial data

Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data

29 March 2018
P. Schratz
Jannes Muenchow
E. Iturritxa
Jakob Richter
A. Brenning
ArXivPDFHTML

Papers citing "Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data"

12 / 12 papers shown
Title
Estimating the Prediction Performance of Spatial Models via Spatial
  k-Fold Cross Validation
Estimating the Prediction Performance of Spatial Models via Spatial k-Fold Cross Validation
J. Pohjankukka
T. Pahikkala
P. Nevalainen
J. Heikkonen
10
131
0
28 May 2020
Hyperparameters and Tuning Strategies for Random Forest
Hyperparameters and Tuning Strategies for Random Forest
Philipp Probst
Marvin N. Wright
A. Boulesteix
109
1,375
0
10 Apr 2018
Tunability: Importance of Hyperparameters of Machine Learning Algorithms
Tunability: Importance of Hyperparameters of Machine Learning Algorithms
Philipp Probst
B. Bischl
A. Boulesteix
45
608
0
26 Feb 2018
mlrMBO: A Modular Framework for Model-Based Optimization of Expensive
  Black-Box Functions
mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions
B. Bischl
Jakob Richter
Jakob Bossek
Daniel Horn
Janek Thomas
Michel Lang
45
168
0
09 Mar 2017
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and
  Comparison
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison
Randal S. Olson
William La Cava
Patryk Orzechowski
Ryan J. Urbanowicz
J. Moore
197
377
0
01 Mar 2017
Auditing Black-box Models for Indirect Influence
Auditing Black-box Models for Indirect Influence
Philip Adler
Casey Falk
Sorelle A. Friedler
Gabriel Rybeck
C. Scheidegger
Brandon Smith
Suresh Venkatasubramanian
TDI
MLAU
96
288
0
23 Feb 2016
Deep Learning in Finance
Deep Learning in Finance
J. B. Heaton
Nicholas G. Polson
J. Witte
46
167
0
21 Feb 2016
A Random Forest Guided Tour
A Random Forest Guided Tour
Gérard Biau
Erwan Scornet
AI4TS
170
2,768
0
18 Nov 2015
Empirical AUC for evaluating probabilistic forecasts
Empirical AUC for evaluating probabilistic forecasts
Simon Byrne
AI4TS
66
25
0
22 Aug 2015
ranger: A Fast Implementation of Random Forests for High Dimensional
  Data in C++ and R
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright
A. Ziegler
200
2,760
0
18 Aug 2015
OpenML: networked science in machine learning
OpenML: networked science in machine learning
Joaquin Vanschoren
Jan N. van Rijn
B. Bischl
Luís Torgo
FedML
AI4CE
93
1,310
0
29 Jul 2014
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with
  Application to Active User Modeling and Hierarchical Reinforcement Learning
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
E. Brochu
Vlad M. Cora
Nando de Freitas
GP
108
2,437
0
12 Dec 2010
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