Difference between revisions of "APB-ML-mlr"

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<div style="padding:5px; border:1px solid #000000; background-color:#f2fafa; font-size:300%; font-weight:400; color: #000000; width:100%;">
 
The mlr R Package
 
The mlr R Package
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((Draft) ...)
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<div class="keywords">
 
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<b>Keywords:</b>&nbsp;
 
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(Draft) ...
 
 
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__TOC__
 
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<b>Abstract:</b><br />
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== Abstract ==
 
 
<section begin=abstract />
 
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "abstract" -->
 
 
(Draft only: edit during development) The R mlr package for diverse machine learning algorithms.
 
(Draft only: edit during development) The R mlr package for diverse machine learning algorithms.
 
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<!-- ============================ -->
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== This unit ... ==
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=== Prerequisites ===
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "prerequisites" -->
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<b>Objectives:</b><br />
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*[http://steipe.biochemistry.utoronto.ca/abc/students/index.php/APB-ML-Measuring_performance APB-ML-Measuring_performance (Quantifying Machine Learning Performance)]
 
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=== Objectives ===
 
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "objectives" -->
 
 
...
 
...
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<b>Outcomes:</b><br />
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=== Outcomes ===
 
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "outcomes" -->
 
 
...
 
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<!-- ============================ -->
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=== Deliverables ===
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "deliverables" -->
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<b>Deliverables:</b><br />
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<section begin=deliverables />
 
<!-- included from "./data/ABC-unit_components.txt", section: "deliverables-time_management" -->
 
<!-- included from "./data/ABC-unit_components.txt", section: "deliverables-time_management" -->
 
*<b>Time management</b>: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
 
*<b>Time management</b>: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
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<!-- included from "./data/ABC-unit_components.txt", section: "deliverables-insights" -->
 
*<b>Insights</b>: If you find something particularly noteworthy about this unit, make a note in your [[ABC-Insights|'''insights!''' page]].
 
*<b>Insights</b>: If you find something particularly noteworthy about this unit, make a note in your [[ABC-Insights|'''insights!''' page]].
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<b>Prerequisites:</b><br />
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*[http://steipe.biochemistry.utoronto.ca/abc/students/index.php/APB-ML-Measuring_performance APB-ML-Measuring_performance (Quantifying Machine Learning Performance)]
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<section end=prerequisites />
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== Contents ==
 
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "contents" -->
 
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...
 
  
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== Further reading, links and resources ==
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<div class="reference-box">[http://www.ncbi.nlm.nih.gov]</div>
 
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== Notes ==
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "notes" -->
 
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== Contents ==
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<!-- included from "./components/APB-ML-mlr.components.txt", section: "contents" -->
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...
 
== Self-evaluation ==
 
== Self-evaluation ==
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=== Question 1===
 
=== Question 1===
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== Further reading, links and resources ==
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Revision as of 19:31, 26 January 2018

The mlr R Package

((Draft) ...)


 


Abstract:

(Draft only: edit during development) The R mlr package for diverse machine learning algorithms.

Objectives:
...

Outcomes:
...

Deliverables:

  • Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
  • Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don't overlook these.
  • Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page.

Prerequisites:


 


Sorry!

This page is only a stub; it is here as a placeholder to establish the logical framework of the site but there is no significant content as yet. Do not work with this material until it is updated to "live" status.


 



 


Contents

...

Self-evaluation

Notes

Further reading, links and resources

 



 

If in doubt, ask! If anything about this learning unit is not clear to you, do not proceed blindly but ask for clarification. Post your question on the course mailing list: others are likely to have similar problems. Or send an email to your instructor.


 

About ...
 
Author:

NN <email@host>

Created:

2017-09-17

Modified:

2017-09-18

Version:

0.1

Version history:

  • 0.1 First stub

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