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Improved description of max_iterations
in documentation
#1212
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Codecov Report
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Coverage 99.92% 99.92%
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Files 196 196
Lines 12029 12029
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Hits 12020 12020
Misses 9 9 Continue to review full report at Codecov.
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Thanks @christopherbunn ! Left two suggested tweaks but LGTM
docs/source/start.ipynb
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@@ -46,6 +46,8 @@ | |||
"source": [ | |||
"EvalML has many options to configure the pipeline search. At the minimum, we need to define an objective function. For simplicity, we will use the F1 score in this example. However, the real power of EvalML is in using domain-specific [objective functions](user_guide/objectives.ipynb) or [building your own](user_guide/objectives.ipynb).\n", | |||
"\n", | |||
"In addition, EvalML provides a number of parameters to control the search process. `max_iterations` is one of the parameters which controls the stopping criterion for the AutoML search. It indicates the maximum number of pipelines to train and evaluate. In this example, `max_iterations` is set to 5. \n", |
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Thanks!
Can you move this below the next line "Below EvalML utilizes "? I think it reads easier. Also I suggest you delete "In addition, "
docs/source/user_guide/automl.ipynb
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@@ -61,7 +61,7 @@ | |||
"source": [ | |||
"The AutoML search will log its progress, reporting each pipeline and parameter set evaluated during the search.\n", | |||
"\n", | |||
"By default, AutoML will search a fixed number of pipeline and parameter pairs (5). The first pipeline to be evaluated will always be a baseline model representing a trivial solution." | |||
"There are a number of mechanisms to control the AutoML search time. One way is to set the maximum number of iterations using `max_iterations`. By default, AutoML will search a fixed number of iterations and parameter pairs (`max_iterations=5`). The first pipeline to be evaluated will always be a baseline model representing a trivial solution. " |
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Suggest replace "One way is to set the maximum number of iterations" with "One way is to set the maximum number of candidate models to be evaluated during AutoML"
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Resolves #1203