Default NuPIC Configuration

Default values for some NuPIC components are stored in src/nupic/support/nupic-default.xml.

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!-- Do not modify this file directly.  Instead, copy entries that you -->
<!-- wish to modify from this file into nupic-site.xml and change them -->
<!-- there.  If nupic-site.xml does not already exist, create it.      -->

<configuration>

<property>
  <name>nupic.opf.sdrClassifier.implementation</name>
  <value>cpp</value>
  <description>The SDR classifier implementation to use by default. The current
  options are 'py' and 'cpp'.
  </description>
</property>

<property>
  <name>nupic.opf.metricWindow</name>
  <value>1000</value>
  <description> The number of records over which average metrics
  (eror, Grok Score, etc.) are computed. Must be greater than 1.
  </description>
</property>


<!-- Anomaly Classification Properties -->
<property>
  <name>nupic.model.temporalAnomaly.wait_records</name>
  <value>4000</value>
  <description> The number of records to wait before classification begins.
  Used to wait for anomaly scores to settle down before classifying anomalies. 
  </description>
</property>

<property>
  <name>nupic.model.temporalAnomaly.auto_detect_threshold</name>
  <value>1.1</value>
  <description>Threshold on the anomaly score used to identify anomalies.
  Anomaly score ranges are between 0 and 1. If this value is set above 1, it
  is the equivalent of turning auto classification off.
  </description>
</property>

<property>
  <name>nupic.model.temporalAnomaly.window_length</name>
  <value>10000</value>
  <description>The number of records back to store relevent information for
  anomaly classification. These records will be recalculated when labels or
  thresholds are updated.
  </description>
</property>

<property>
  <name>nupic.model.temporalAnomaly.anomaly_vector</name>
  <value>tpc</value>
  <description>Vector type used to classify anomalies. Types:
    tpc - classify on active cells in the TP
    sp_tpe - classify on the active SP columns concatenated with the predicted
      TM columns that did not become active
  </description>
</property>

<!-- database credentials, used for swarming -->

<property>
  <name>nupic.cluster.database.host</name>
  <value>localhost</value>
  <description>Name of the machine running the MySQL database server</description>
</property>

<property>
  <name>nupic.cluster.database.user</name>
  <value>root</value>
  <description>Username for the MySQL database server </description>
</property>

<property>
  <name>nupic.cluster.database.port</name>
  <value>3306</value>
  <description>Port number for the MySQL database server </description>
</property>

<property>
  <name>nupic.cluster.database.passwd</name>
  <value></value>
  <description>Password for the MySQL database server </description>
</property>

<property>
  <name>nupic.cluster.database.nameSuffix</name>
  <value>${env.USER}</value>
  <description>Suffix to place at the end of each database name.
  </description>
</property>

<!-- Model checkpoint settings -->
<property>
  <name>nupic.model.checkpoint.maxPredictionRows</name>
  <value>50000</value>
  <description> Maximum number of prediction rows to save along with model
  checkpoints.
  </description>
</property>

<!--Hypersearch parameters-->
<property>
  <name>nupic.hypersearch.minParticlesPerSwarm</name>
  <value>5</value>
  <description>The minimum number of particles to create per swarm
  </description>
</property>

<property>
  <name>nupic.hypersearch.speculative.particles.default</name>
  <value>1</value>
  <description>If true (not 0), hypersearch workers will go ahead and create
  and run particles in subsequent sprints and generations before the current
  generation or sprint has been completed. If false, a worker will wait in a
  sleep loop until the current generation or sprint has finished before
  choosing the next particle position or going into the next sprint. When true,
  the best model can be found faster, but results are less repeatable due to
  the randomness of when each worker completes each particle. This property
  can be overridden via the speculativeParticles element of the Hypersearch
  job params.
  </description>
</property>

<property>
  <name>nupic.hypersearch.max.field.branching</name>
  <value>5</value>
  <description>If > 0 at every sprint only the top n fields from the pair
  sprint will be appended to the best model from the previous sprint. Usefull
  feature for datasets with many fields. Also limits the maximum number of fields
  that can be in the best model to this n.
  </description>
</property>

<property>
  <name>nupic.hypersearch.min.field.contribution</name>
  <value>0.2</value>
  <description>When adding fields in sprints only looks at fields that by themselves
  contribute at least by n percent to improving the error
  </description>
</property>

<property>
  <name>nupic.hypersearch.speculative.particles.sleepSecondsMax</name>
  <value>10.0</value>
  <description>
  When a worker sleeps to honor nupic.hypersearch.speculative.particles, it
  will sleep for a random amount of time between 0 and this value.
  </description>
</property>

<property>
  <name>nupic.hypersearch.maxUniqueModelAttempts</name>
  <value>10</value>
  <description>The max # of attempts we will make to create a unique model before
    giving up and assuming all the possible positions in a swarm have been
    evaluated.
  </description>
</property>

<property>
  <name>nupic.hypersearch.modelOrphanIntervalSecs</name>
  <value>180</value>
  <description>The max amount of time (in seconds) allowed before a model is
  considered orphaned. At this point, it is available for being taken over
  by another worker.
  </description>
</property>

<property>
  <name>nupic.hypersearch.maxPctErrModels</name>
  <value>0.20</value>
  <description>If this percent of the models in a hyperseach completed with
  an error, abort the search.
  </description>
</property>

<property>
  <name>nupic.hypersearch.inertia</name>
  <value>0.25</value>
  <description>Weight given to the previous velocity of a particle in PSO.
  </description>
</property>

<property>
  <name>nupic.hypersearch.cogRate</name>
  <value>0.25</value>
  <description>This parameter controls how much the particle is affected by its
  distance from it's local best position.
  </description>
</property>

<property>
  <name>nupic.hypersearch.socRate</name>
  <value>1.0</value>
  <description>This parameter controls how much the particle is affected by its
  distance from the global best position.
  </description>
</property>


<property>
  <name>nupic.hypersearch.randomUpperBound</name>
  <value>1.2</value>
  <description>Upper bound for sampling a random number in the PSO.
  </description>
</property>

<property>
  <name>nupic.hypersearch.randomLowerBound</name>
  <value>0.8</value>
  <description>Lower bound for sampling a random number in the PSO.
  </description>
</property>


<!-- Model Chooser Properties -->
<property>
  <name>nupic.hypersearch.bestModelMinRecords</name>
  <value>1000</value>
  <description> The minimum number of records for a model to be a candidate for
  the 'best model' in a hypersearch job
  </description>
</property>


<!-- Model Maturity/Termination properties -->
<property>
  <name>nupic.hypersearch.enableModelMaturity</name>
  <value>0</value>
  <description> Feature flag to enable model maturity. If set to 1, models can
  be stopped early if their error scores level off. Otherwise, all models will
  run till they are killed or until they run out of data
  </description>
</property>


<property>
  <name>nupic.hypersearch.maturityNumPoints</name>
  <value>10</value>
  <description> The number of points that model runner looks at to determine if
  the model has matured. For example, if set to 10, the model runner will look at
  the change over the LAST 10 points to see if the model has matured
  </description>
</property>

<property>
  <name>nupic.hypersearch.maturityPctChange</name>
  <value>0.005</value>
  <description> Model maturity is determined by the averege percent change error
  over time. This sets the maximum percent change (positive or negative) that a
  model can have and still be considered 'mature'.
  </description>
</property>


<property>
  <name>nupic.hypersearch.enableSwarmTermination</name>
  <value>0</value>
  <description> Feature flag to enable swarm early termination. If set to 1,
  poorly performing swarms (field combinations) will killed before the swarm
  reaches maturation. 'Poor performance' is defined relative to other swarms
  in the hypersearch
  </description>
</property>

<property>
  <name>nupic.hypersearch.swarmMaturityWindow</name>
  <value>2</value>
  <description> If the best model for a swarm has remained unchanged for this
  many generations, the swarm is considered mature.
  </description>
</property>

<property>
  <name>nupic.hypersearch.swarmMaxGenerations</name>
  <value>10</value>
  <description> The maximum number of generations a swarm (pso optimization)
  can evolve before it is considered mature. Set to -1 to indicate infinite
  generations.
  </description>
</property>

<property>
  <name>nupic.hypersearch.minWorkersPerSwarm</name>
  <value>1</value>
  <description> The minimum workers to allocate per swarm.
  </description>
</property>

<property>
  <name>nupic.hypersearch.maxWorkersPerSwarm</name>
  <value>0</value>
  <description> The maximum workers to allocate per swarm. Set to 0 to fall
    back to "nupic.scheduler.default.maxSlotsPerJob".
  </description>
</property>

<!-- Ensemble Properties-->

<property>
  <name>nupic.hypersearch.ensemble</name>
  <value>0</value>
  <description>If 1, predictions from every model are saved in hbase.
  </description>
</property>

<property>
  <name>nupic.hypersearch.minWorkersPerEnsemble</name>
  <value>1</value>
  <description> The minimum workers to allocate per ensemble.
  </description>
</property>

<property>
  <name>nupic.hypersearch.maxWorkersPerEnsemble</name>
  <value>1</value>
  <description> The maximum workers to allocate for an ensemble.
  </description>
</property>



</configuration>