The SUMO toolbox
2018a
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Uses the Efficient Global Optimization (EGO) algorithm to optimize in hyperparameter space. More...
Public Member Functions | |
function | EGOModelBuilder (var config) |
Class constructor. More... | |
function | runLoop () |
Uses EGO to generate new models. More... | |
function | createMovie () |
Creates a movie of the best models versus the sample or model iteration. More... | |
function | defaultFitnessFunction (var pop, var train) |
Return the score of the given models or parameter vector (representing one or more models). More... | |
function | generateNewModels (var number, var wantModels, var previousPop) |
Generates starting points for the hyperparameter optimization. More... | |
function | observe (var tag, var x_value, var object) |
Observe each observable. More... | |
function | printBestResults () |
Print information about the best modeling results so far. More... | |
function | rebuildBestModel (var keepOldModels) |
Each time new samples are added, the last x best models are re-evaluated against all measures. More... | |
function | registerObserver (var tag, var x_name, var description, var observables) |
Register a new observable. More... | |
function | scoreModels (var models) |
Attaches a score to a given set of models. More... | |
function | setData (var state) |
Set the data point (samples and values) on the ModelBuilder object. More... | |
function | setModelInfo (var model, var score) |
Set important contextual information on the model: the input names, output names, transformation values, measure data, etc. More... | |
function | done () |
This function returns true if all final targets were met. More... | |
function | getBestModel () |
Return the last best model built. More... | |
function | getBestModelScore () |
Get the Global score of the best model. More... | |
function | getBestModels (var n) |
Return the `n' last best models, optionally filtered for one output. More... | |
function | getData () |
Get current samples en values, i.e. More... | |
function | getState () |
Get the complete current state structure. More... | |
function | getKeepOldModels () |
Should old models be kept when managing the model trace. More... | |
function | clearBestModels () |
Clears the best model trace. More... | |
function | getMaximumTime () |
Get the maximum running time. More... | |
function | getOutputDirectory () |
Get the output directory. More... | |
function | getModelFactory () |
Get the ModelFactory. More... | |
function | getNumObjectives () |
Returns the number of objectives the model builder has to deal with (if they are not combined) This corresponds to the number of enabled measures. More... | |
function | getOutputNames () |
Returns the output names. More... | |
function | getParallelMode () |
Returns whether we are running in parallel mode. More... | |
function | getParetoMode () |
Returns whether we are doing multiobjective optimization. More... | |
function | getRestartStrategy () |
Returns the restart strategy we are using. More... | |
function | getStartTime () |
Returns the time we started. More... | |
function | isSamplingEnabled () |
Returns whether adaptive sampling is enabled. More... | |
function | setLevelPlotObject (var levelObj) |
Sets a LevelPlot object. More... | |
function | setModelFactory (var mf) |
Sets a ModelFactory object. More... | |
function | setRunNumber (var number) |
Sets the run number. More... | |
function | setStartTime (var time, var maxTime) |
Sets the start time. More... | |
function | evaluateMeasures (var model) |
This function evaluates the model on all the measures and returns the scores. More... | |
Uses the Efficient Global Optimization (EGO) algorithm to optimize in hyperparameter space.
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inline |
Class constructor.
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inlineinherited |
Clears the best model trace.
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inherited |
Creates a movie of the best models versus the sample or model iteration.
Create a quicktime movie of all the .jpeg files in the output directory.
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inherited |
Return the score of the given models or parameter vector (representing one or more models).
This is a generic implementation that every model builder can use.
pop | population of sumo models |
train | do we want to fit the sumo models (boolean) |
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inlineinherited |
This function returns true if all final targets were met.
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inherited |
This function evaluates the model on all the measures and returns the scores.
It also calculates the global score of the model, based on a combination of the (weighted) separate measure scores.
model | sumo Model |
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inherited |
Generates starting points for the hyperparameter optimization.
Also implements different restart strategies (= i.e.
number | number of points to generate |
wantModels | wrap the points in sumo models (boolean) |
previousPop | previous sumo population |
how to continue the hyperparameter optimization process in the next modeling iteration)
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inlineinherited |
Return the last best model built.
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inlineinherited |
Return the `n' last best models, optionally filtered for one output.
n | number of sumo models to retrieve |
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inlineinherited |
Get the Global score of the best model.
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inlineinherited |
Get current samples en values, i.e.
the samples and values of all simulations ran up till now.
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inlineinherited |
Should old models be kept when managing the model trace.
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inlineinherited |
Get the maximum running time.
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inlineinherited |
Get the ModelFactory.
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inlineinherited |
Returns the number of objectives the model builder has to deal with (if they are not combined) This corresponds to the number of enabled measures.
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inlineinherited |
Get the output directory.
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inlineinherited |
Returns the output names.
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inlineinherited |
Returns whether we are running in parallel mode.
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inlineinherited |
Returns whether we are doing multiobjective optimization.
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inlineinherited |
Returns the restart strategy we are using.
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inlineinherited |
Returns the time we started.
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inlineinherited |
Get the complete current state structure.
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inlineinherited |
Returns whether adaptive sampling is enabled.
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inherited |
Observe each observable.
Records the values in the matching profilers.
tag | profiles to write to (e.g., all profilers starting with 'best') |
x_value | x value to profile |
object | y value to profile |
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inherited |
Print information about the best modeling results so far.
Includes the best model score, type of error function, target, etc.
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inherited |
Each time new samples are added, the last x best models are re-evaluated against all measures.
rebuildBestModels ensures lucky models (on the new data) to be kept.
keepOldModels | keep the old model trace (boolean) |
The best of these is set as the new best model
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inherited |
Register a new observable.
Only registers the profiler if it is enabled in the configuration.
tag | profiles to write to (e.g., all profilers starting with 'best') |
x_name | name of the x-axis |
description | description of the observable |
observables | cell array of Observable objects |
function runLoop | ( | ) |
Uses EGO to generate new models.
TODO.
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inherited |
Attaches a score to a given set of models.
Calls all Measure object attached to the ModelBuilder.
models | cell array of sumo models |
Afterwards, the sumo models are ordered based on the score.
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inherited |
Set the data point (samples and values) on the ModelBuilder object.
New data for a ModelBuilder passes through here.
state | struct |
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inlineinherited |
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inlineinherited |
Sets a ModelFactory object.
mf | ModelFactory object |
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inherited |
Set important contextual information on the model: the input names, output names, transformation values, measure data, etc.
This is information only the modelbuilder has.
model | sumo Model |
score | score |
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inlineinherited |
Sets the run number.
number | run number. |
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inlineinherited |
Sets the start time.
time | start time |
maxTime | maximum time we are allowed to run |