_id stringlengths 2 7 | title stringclasses 1
value | partition stringclasses 3
values | text stringlengths 6 2.61k | language stringclasses 1
value | meta_information dict |
|---|---|---|---|---|---|
c164700 | train | // newHealthChecker returns the healthz handler. The handler runs until the
// provided context is canceled. | {
"resource": ""
} | ||
c164701 | train | // runHealthCheck performs a single health check and makes the result available
// for any clients performing and HTTP request against the healthChecker. | {
"resource": ""
} | ||
c164702 | train | // handleAuthorization handles the OAuth2 auth endpoint. | {
"resource": ""
} | ||
c164703 | train | // finalizeLogin associates the user's identity with the current AuthRequest, then returns
// the approval page's path. | {
"resource": ""
} | ||
c164704 | train | // Check for username prompt override from connector. Defaults to "Username". | {
"resource": ""
} | ||
c164705 | train | // NewServer constructs a server from the provided config. | {
"resource": ""
} | ||
c164706 | train | // newKeyCacher returns a storage which caches keys so long as the next | {
"resource": ""
} | ||
c164707 | train | // openConnector will parse the connector config and open the connector. | {
"resource": ""
} | ||
c164708 | train | // OpenConnector updates server connector map with specified connector object. | {
"resource": ""
} | ||
c164709 | train | // getConnector retrieves the connector object with the given id from the storage
// and updates the connector list for server if necessary. | {
"resource": ""
} | ||
c164710 | train | // Open returns an authentication strategy using Keystone. | {
"resource": ""
} | ||
c164711 | train | // Open returns a strategy for logging in through GitHub. | {
"resource": ""
} | ||
c164712 | train | // newHTTPClient returns a new HTTP client that trusts the custom delcared rootCA cert. | {
"resource": ""
} | ||
c164713 | train | // getGroups retrieves GitHub orgs and teams a user is in, if any. | {
"resource": ""
} | ||
c164714 | train | // formatTeamName returns unique team name.
// Orgs might have the same team names. To make team name unique it should be prefixed with the org name. | {
"resource": ""
} | ||
c164715 | train | // userOrgs retrieves list of current user orgs | {
"resource": ""
} | ||
c164716 | train | // userOrgTeams retrieves teams which current user belongs to.
// Method returns a map where key is an org name and value list of teams under the org. | {
"resource": ""
} | ||
c164717 | train | // Filter the users' team memberships by 'teams' from config. | {
"resource": ""
} | ||
c164718 | train | // Open returns an authentication strategy using LDAP. | {
"resource": ""
} | ||
c164719 | train | // OpenConnector is the same as Open but returns a type with all implemented connector interfaces. | {
"resource": ""
} | ||
c164720 | train | // do initializes a connection to the LDAP directory and passes it to the
// provided function. It then performs appropriate teardown or reuse before
// returning. | {
"resource": ""
} | ||
c164721 | train | // GetCrossValidatedMetric returns the mean and variance of the confusion-matrix-derived
// metric across all folds. | {
"resource": ""
} | ||
c164722 | train | // GenerateCrossFoldValidationConfusionMatrices divides the data into a number of folds
// then trains and evaluates the classifier on each fold, producing a new ConfusionMatrix. | {
"resource": ""
} | ||
c164723 | train | // Attributes returns a slice of Attributes in this BinaryAttributeGroup. | {
"resource": ""
} | ||
c164724 | train | // AddAttribute adds an Attribute to this BinaryAttributeGroup | {
"resource": ""
} | ||
c164725 | train | // NewRandomForest generates and return a new random forests
// forestSize controls the number of trees that get built
// features controls the number of features used to build each tree. | {
"resource": ""
} | ||
c164726 | train | // Fit builds the RandomForest on the specified instances | {
"resource": ""
} | ||
c164727 | train | // Predict generates predictions from a trained RandomForest. | {
"resource": ""
} | ||
c164728 | train | // String returns a human-readable representation of this tree. | {
"resource": ""
} | ||
c164729 | train | // This file contains utility functions relating to efficiently
// generating predictions and instantiating DataGrid implementations.
// GeneratePredictionVector selects the class Attributes from a given
// FixedDataGrid and returns something which can hold the predictions. | {
"resource": ""
} | ||
c164730 | train | // GetAttributeByName returns an Attribute matching a given name.
// Returns nil if one doesn't exist. | {
"resource": ""
} | ||
c164731 | train | // GetClassDistributionByBinaryFloatValue returns the count of each row
// which has a float value close to 0.0 or 1.0. | {
"resource": ""
} | ||
c164732 | train | // GetClassDistributionAfterThreshold returns the class distribution
// after a speculative split on a given Attribute using a threshold. | {
"resource": ""
} | ||
c164733 | train | // GetClassDistributionAfterSplit returns the class distribution
// after a speculative split on a given Attribute. | {
"resource": ""
} | ||
c164734 | train | // LazyShuffle randomizes the row order without re-ordering the rows
// via an InstancesView. | {
"resource": ""
} | ||
c164735 | train | // CheckCompatible checks whether two DataGrids have the same Attributes
// and if they do, it returns them. | {
"resource": ""
} | ||
c164736 | train | // CheckStrictlyCompatible checks whether two DenseInstances have
// AttributeGroups with the same Attributes, in the same order,
// enabling optimisations. | {
"resource": ""
} | ||
c164737 | train | // NewBinningFilter creates a BinningFilter structure
// with some helpful default initialisations. | {
"resource": ""
} | ||
c164738 | train | // Train computes and stores the bin values
// for the training instances. | {
"resource": ""
} | ||
c164739 | train | // Transform takes an Attribute and byte sequence and returns
// the transformed byte sequence. | {
"resource": ""
} | ||
c164740 | train | // MarshalAttribute converts an Attribute to a JSON map. | {
"resource": ""
} | ||
c164741 | train | // DeserializeAttributes constructs a ve | {
"resource": ""
} | ||
c164742 | train | // ReplaceDeserializedAttributeWithVersionFromInstances takes an independently deserialized Attribute and matches it
// if possible with one from a candidate FixedDataGrid. | {
"resource": ""
} | ||
c164743 | train | // ReplaceDeserializedAttributesWithVersionsFromInstances takes some independently loaded Attributes and
// matches them up with a candidate FixedDataGrid. | {
"resource": ""
} | ||
c164744 | train | // NewDenseInstances generates a new DenseInstances set
// with an anonymous EDF mapping and default settings. | {
"resource": ""
} | ||
c164745 | train | // NewStructuralCopy generates an empty DenseInstances with the same layout as
// an existing FixedDataGrid, but with no data. | {
"resource": ""
} | ||
c164746 | train | // NewDenseCopy generates a new DenseInstances set
// from an existing FixedDataGrid. | {
"resource": ""
} | ||
c164747 | train | // CreateAttributeGroup adds a new AttributeGroup to this set of instances
// with a given name. If the size is 0, a bit-ag is added
// if the size of not 0, then the size of each ag attribute
// is set to that number of bytes. | {
"resource": ""
} | ||
c164748 | train | // AllAttributeGroups returns a copy of the available AttributeGroups | {
"resource": ""
} | ||
c164749 | train | // AddAttributeToAttributeGroup adds an Attribute to a given ag | {
"resource": ""
} | ||
c164750 | train | // AllAttributes returns a slice of all Attributes. | {
"resource": ""
} | ||
c164751 | train | // AddClassAttribute sets an Attribute to be a class Attribute. | {
"resource": ""
} | ||
c164752 | train | // RemoveClassAttribute removes an Attribute from the set of class Attributes. | {
"resource": ""
} | ||
c164753 | train | // AllClassAttributes returns a slice of Attributes which have
// been designated class Attributes. | {
"resource": ""
} | ||
c164754 | train | //
// Allocation functions
//
// realiseAttributeGroups decides which Attributes are going
// to be stored in which groups | {
"resource": ""
} | ||
c164755 | train | // MapOverRows passes each row map into a function.
// First argument is a list of AttributeSpec in the order
// they're needed in for the function. The second is the function
// to call on each row. | {
"resource": ""
} | ||
c164756 | train | // Size returns the number of Attributes as the first return value
// and the maximum allocated row as the second value. | {
"resource": ""
} | ||
c164757 | train | // swapRows swaps over rows i and j | {
"resource": ""
} | ||
c164758 | train | // String returns a human-readable summary of this dataset. | {
"resource": ""
} | ||
c164759 | train | // NewFloatConvertFilter creates a blank FloatConvertFilter | {
"resource": ""
} | ||
c164760 | train | // MarshalJSON returns a JSON representation of this Attribute
// for serialisation. | {
"resource": ""
} | ||
c164761 | train | // UnmarshalJSON reads a JSON representation of this Attribute. | {
"resource": ""
} | ||
c164762 | train | // Equals tests a FloatAttribute for equality with another Attribute.
//
// Returns false if the other Attribute has a different name
// or if the other Attribute is not a FloatAttribute. | {
"resource": ""
} | ||
c164763 | train | // CheckSysValFromString confirms whether a given rawVal can
// be converted into a valid system representation. If it can't,
// the returned value is nil. | {
"resource": ""
} | ||
c164764 | train | // GetStringFromSysVal converts a given system value to to a string with two decimal
// places of precision. | {
"resource": ""
} | ||
c164765 | train | // NewNetwork creates a new Network containing size neurons,
// with a certain number dedicated to input, and a pre-defined
// neural function applied to the rest.
//
// Input nodes are set to have a Linear NeuralFunction and are
// connected to themselves for propagation. | {
"resource": ""
} | ||
c164766 | train | // String gets a human-readable representation of this network. | {
"resource": ""
} | ||
c164767 | train | // generateTrainingAttrs selects RandomFeatures number of base.Attributes from
// the provided base.Instances. | {
"resource": ""
} | ||
c164768 | train | // generatePredictionInstances returns a modified version of the
// requested base.Instances with only the base.Attributes selected
// for training the model. | {
"resource": ""
} | ||
c164769 | train | // generateTrainingInstances generates RandomFeatures number of
// attributes and returns a modified version of base.Instances
// for training the model | {
"resource": ""
} | ||
c164770 | train | // AddModel adds a base.Classifier to the current model | {
"resource": ""
} | ||
c164771 | train | // Fit generates and trains each model on a randomised subset of
// Instances. | {
"resource": ""
} | ||
c164772 | train | // String returns a human-readable representation of the
// BaggedModel and everything it contains | {
"resource": ""
} | ||
c164773 | train | // InnerProduct computes a Eucledian inner product. | {
"resource": ""
} | ||
c164774 | train | // ParseCSVGetRows returns the number of rows in a given file. | {
"resource": ""
} | ||
c164775 | train | // ParseCSVEstimateFilePrecision determines what the maximum number of
// digits occuring anywhere after the decimal point within the file. | {
"resource": ""
} | ||
c164776 | train | // ParseCSVGetAttributes returns an ordered slice of appropriate-ly typed
// and named Attributes. | {
"resource": ""
} | ||
c164777 | train | // ParseCSVSniffAttributeNames returns a slice containing the top row
// of a given CSV file, or placeholders if hasHeaders is false. | {
"resource": ""
} | ||
c164778 | train | // ParseCSVSniffAttributeTypes returns a slice of appropriately-typed Attributes.
//
// The type of a given attribute is determined by looking at the first data row
// of the CSV. | {
"resource": ""
} | ||
c164779 | train | // ParseCSVToInstances reads the CSV file given by filepath and returns
// the read Instances. | {
"resource": ""
} | ||
c164780 | train | // ParseCSVToInstancesTemplated reads the CSV file given by filepath and returns
// the read Instances, using another already read DenseInstances as a template. | {
"resource": ""
} | ||
c164781 | train | // ParseCSVToInstancesWithAttributeGroups reads the CSV file given by filepath,
// and returns the read DenseInstances, but also makes sure to group any Attributes
// specified in the first argument and also any class Attributes specified in the second | {
"resource": ""
} | ||
c164782 | train | // Create a new Bernoulli Naive Bayes Classifier. The argument 'classes'
// is the number of possible labels in the classification task. | {
"resource": ""
} | ||
c164783 | train | // Invert returns an alternative form of cluster map where the key represents the point
// index and the value represents the cluster index it's assigned to | {
"resource": ""
} | ||
c164784 | train | // AddAttribute adds the AttributeSpec of the given attribute `a'
// to the AbstractFloatFilter for discretisation. | {
"resource": ""
} | ||
c164785 | train | // Distance computes the Manhattan distance, also known as L1 distance.
// == the sum of the absolute values of elements. | {
"resource": ""
} | ||
c164786 | train | // NewLazilyFitleredInstances returns a new FixedDataGrid after
// applying the given Filter to the Attributes it includes. Unfiltered
// Attributes are passed through without modification. | {
"resource": ""
} | ||
c164787 | train | // GetAttribute returns an AttributeSpecification for a given Attribute | {
"resource": ""
} | ||
c164788 | train | // AllAttributes returns every Attribute defined in the source datagrid,
// in addition to the revised Attributes created by the filter. | {
"resource": ""
} | ||
c164789 | train | // AllClassAttributes returns details of all Attributes currently specified
// as being class Attributes.
//
// If applicable, the Attributes returned are those after modification
// by the Filter. | {
"resource": ""
} | ||
c164790 | train | // Get returns a transformed byte slice stored at a given AttributeSpec and row. | {
"resource": ""
} | ||
c164791 | train | // MapOverRows maps an iteration mapFunc over the bytes contained in the source
// FixedDataGrid, after modification by the filter. | {
"resource": ""
} | ||
c164792 | train | // String returns a human-readable summary of this FixedDataGrid
// after filtering. | {
"resource": ""
} | ||
c164793 | train | // GenerateSplitRule returns the best attribute out of those randomly chosen
// which maximises Information Gain | {
"resource": ""
} | ||
c164794 | train | // NewRandomTree returns a new RandomTree which considers attrs randomly
// chosen attributes at each node. | {
"resource": ""
} | ||
c164795 | train | // Fit builds a RandomTree suitable for prediction | {
"resource": ""
} | ||
c164796 | train | // Predict returns a set of Instances containing predictions | {
"resource": ""
} | ||
c164797 | train | // Save outputs this model to a file | {
"resource": ""
} | ||
c164798 | train | // SaveWithPrefix outputs this model to a file with a prefix. | {
"resource": ""
} | ||
c164799 | train | // Load retrieves this model from a file | {
"resource": ""
} |
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