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Papers: 10.1371/journal.pone.0216511

https://doi.org/10.1371/journal.pone.0216511

Modelling tick bite risk by combining random forests and count data regression models

Cited by: 10
Author(s): Irene Garcia‐Martí, R. Zurita-Milla, Arno Swart
Published: over 5 years ago

Software Mentions 8

pypi: Cartopy
A Python library for cartographic visualizations with Matplotlib
Papers that mentioned: 10
Very Likely Science (90)
pypi: GDAL
GDAL: Geospatial Data Abstraction Library
Papers that mentioned: 71
Very Likely Science (90)
pypi: matplotlib
Python plotting package
Papers that mentioned: 1,045
Very Likely Science (100)
pypi: numpy
Fundamental package for array computing in Python
Papers that mentioned: 832
Very Likely Science (100)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)
pypi: scipy
Fundamental algorithms for scientific computing in Python
Papers that mentioned: 1,071
Very Likely Science (100)
pypi: SkillMetrics
A Python library for calculating and displaying the skill of model predictions against observations.
Papers that mentioned: 1
Very Likely Science (65)
pypi: statsmodels
Statistical computations and models for Python
Papers that mentioned: 277
Very Likely Science (90)