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Microsoft Azure Machine Learning

You're reading from  Microsoft Azure Machine Learning

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781784390792
Pages 212 pages
Edition 1st Edition
Languages
Authors (2):
Sumit Mund Sumit Mund
Profile icon Sumit Mund
Christina Storm Christina Storm
Profile icon Christina Storm
View More author details
Toc

Table of Contents (21) Chapters close

Microsoft Azure Machine Learning
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Introduction ML Studio Inside Out Data Exploration and Visualization Getting Data in and out of ML Studio Data Preparation Regression Models Classification Models Clustering A Recommender System Extensibility with R and Python Publishing a Model as a Web Service Case Study Exercise I Case Study Exercise II Index

The dataset


You can download the dataset and find the description at https://www.kaggle.com/c/afsis-soil-properties/data.

The dataset has been explained in the following term list, as found at the preceding web link:

  • PIDN: This is the unique soil sample identifier.

  • SOC: This refers to soil organic carbon.

  • pH: These are the pH values.

  • Ca: This is the Mehlich-3 extractable calcium.

  • P: This is the Mehlich-3 extractable phosphorus.

  • Sand: This is the sand content.

  • m7497.96 - m599.76: There are 3,578 mid-infrared absorbance measurements. For example, the "m7497.96" column is the absorbance at wavenumber 7497.96 cm-1. We suggest you remove spectra CO2 bands, which are in the region m2379.76 to m2352.76, but you do not have to.

  • Depth: This is the depth of the soil sample (this has two categories: "Topsoil" and "Subsoil"). They have also included some potential spatial predictors from remote sensing data sources. Short variable descriptions of different terms are provided below and additional descriptions...

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