_id stringlengths 2 7 | title stringclasses 1
value | partition stringclasses 3
values | text stringlengths 6 2.61k | language stringclasses 1
value | meta_information dict |
|---|---|---|---|---|---|
c164800 | train | // LoadWithPrefix retrives this random tree from disk with a given prefix. | {
"resource": ""
} | ||
c164801 | train | // GetMetadata returns required serialization metadata | {
"resource": ""
} | ||
c164802 | train | // GetNamedFile returns a file named a given thing from the tar file. If there's more than one
// entry, the most recent is returned. | {
"resource": ""
} | ||
c164803 | train | // ReadMetadataAtPrefix reads the METADATA file after prefix. If an error is returned, the first value is undefined. | {
"resource": ""
} | ||
c164804 | train | // ReadSerializedClassifierStub is the counterpart of CreateSerializedClassifierStub.
// It's used inside SaveableClassifiers to read information from a perviously saved
// model file. | {
"resource": ""
} | ||
c164805 | train | // GetBytesForKey returns the bytes at a given location in the output. | {
"resource": ""
} | ||
c164806 | train | // GetJSONForKey deserializes a JSON key in the output file. | {
"resource": ""
} | ||
c164807 | train | // GetInstancesForKey deserializes some instances stored in a classifier output file | {
"resource": ""
} | ||
c164808 | train | // GetUInt64ForKey returns a int64 stored at a given key | {
"resource": ""
} | ||
c164809 | train | // GetAttributeForKey returns an Attribute stored at a given key | {
"resource": ""
} | ||
c164810 | train | // GetAttributesForKey returns an Attribute list stored at a given key | {
"resource": ""
} | ||
c164811 | train | // Close finalizes the Classifier serialization session. | {
"resource": ""
} | ||
c164812 | train | // WriteBytesForKey creates a new entry in the serializer file with some user-defined bytes. | {
"resource": ""
} | ||
c164813 | train | // WriteU64ForKey creates a new entry in the serializer file with the bytes of a uint64 | {
"resource": ""
} | ||
c164814 | train | // WriteJSONForKey creates a new entry in the file with an interface serialized as JSON. | {
"resource": ""
} | ||
c164815 | train | // WriteAttributeForKey creates a new entry in the file containing a serialized representation of Attribute | {
"resource": ""
} | ||
c164816 | train | // WriteAttributesForKey does the same as WriteAttributeForKey, just with more than one Attribute. | {
"resource": ""
} | ||
c164817 | train | // WriteInstances for key creates a new entry in the file containing some training instances | {
"resource": ""
} | ||
c164818 | train | // WriteMetadataAtPrefix outputs a METADATA entry in the right place | {
"resource": ""
} | ||
c164819 | train | // CreateSerializedClassifierStub generates a file to serialize into
// and writes the METADATA header. | {
"resource": ""
} | ||
c164820 | train | // param base.IFixedDataGrid
// return base.IFixedDataGrid | {
"resource": ""
} | ||
c164821 | train | // Copy return s a copy of these parameters | {
"resource": ""
} | ||
c164822 | train | // SetKindFromStrings configures the solver kind from strings.
// Penalty and Loss parameters can either be l1 or l2. | {
"resource": ""
} | ||
c164823 | train | // convertToNativeFormat converts the LinearSVCParams given into a format
// for liblinear. | {
"resource": ""
} | ||
c164824 | train | // NewLinearSVCFromParams constructs a LinearSVC from the given LinearSVCParams structure. | {
"resource": ""
} | ||
c164825 | train | // Save outputs this classifier | {
"resource": ""
} | ||
c164826 | train | // Dot computes dot value of vectorX and vectorY. | {
"resource": ""
} | ||
c164827 | train | // MarshalJSON returns a JSON version of this BinaryAttribute for serialisation. | {
"resource": ""
} | ||
c164828 | train | // GetSysValFromString returns either 1 or 0 in a single byte. | {
"resource": ""
} | ||
c164829 | train | // Equals checks for equality with another BinaryAttribute. | {
"resource": ""
} | ||
c164830 | train | // Compatible checks whether this Attribute can be represented
// in the same pond as another. | {
"resource": ""
} | ||
c164831 | train | // MarshalJSON returns a JSON version of this Attribute. | {
"resource": ""
} | ||
c164832 | train | // UnmarshalJSON returns a JSON version of this Attribute. | {
"resource": ""
} | ||
c164833 | train | // GetSysVal returns the system representation of userVal as an index into the Values slice
// If the userVal can't be found, it returns nothing. | {
"resource": ""
} | ||
c164834 | train | // String returns a human-readable summary of this Attribute.
//
// Returns a string containing the list of human-readable values this
// CategoricalAttribute can take. | {
"resource": ""
} | ||
c164835 | train | // Compatible checks that this CategoricalAttribute has the same
// values as another, in the same order. | {
"resource": ""
} | ||
c164836 | train | // Fit PCA model and transform data
// Need return is base.FixedDataGrid | {
"resource": ""
} | ||
c164837 | train | // Fit PCA model | {
"resource": ""
} | ||
c164838 | train | // Need return is base.FixedDataGrid | {
"resource": ""
} | ||
c164839 | train | //Helpful private functions
//Compute mean of the columns of input matrix | {
"resource": ""
} | ||
c164840 | train | // PackU64ToBytesInline fills ret with the byte values of
// val. Ret must have length at least 8. | {
"resource": ""
} | ||
c164841 | train | // PackFloatToBytesInline fills ret with the byte values of
// the float64 argument. ret must be at least 8 bytes in size. | {
"resource": ""
} | ||
c164842 | train | // PackU64ToBytes allocates a return value of appropriate length
// and fills it with the values of val. | {
"resource": ""
} | ||
c164843 | train | // UnpackBytesToU64 converst a given byte slice into
// a uint64 value. | {
"resource": ""
} | ||
c164844 | train | // UnpackBytesToFloat converts a given byte slice into an
// equivalent float64. | {
"resource": ""
} | ||
c164845 | train | // GetTruePositives returns the number of times an entry is
// predicted successfully in a given ConfusionMatrix. | {
"resource": ""
} | ||
c164846 | train | // GetFalsePositives returns the number of times an entry is
// incorrectly predicted as having a given class. | {
"resource": ""
} | ||
c164847 | train | // GetFalseNegatives returns the number of times an entry is
// incorrectly predicted as something other than the given class. | {
"resource": ""
} | ||
c164848 | train | // GetTrueNegatives returns the number of times an entry is
// correctly predicted as something other than the given class. | {
"resource": ""
} | ||
c164849 | train | // GetPrecision returns the fraction of of the total predictions
// for a given class which were correct. | {
"resource": ""
} | ||
c164850 | train | // GetRecall returns the fraction of the total occurrences of a
// given class which were predicted. | {
"resource": ""
} | ||
c164851 | train | // GetMicroPrecision assesses Classifier performance across
// all classes using the total true positives and false positives. | {
"resource": ""
} | ||
c164852 | train | // GetMacroPrecision assesses Classifier performance across all
// classes by averaging the precision measures achieved for each class. | {
"resource": ""
} | ||
c164853 | train | // GetMicroRecall assesses Classifier performance across all
// classes using the total true positives and false negatives. | {
"resource": ""
} | ||
c164854 | train | // GetMacroRecall assesses Classifier performance across all classes
// by averaging the recall measures achieved for each class | {
"resource": ""
} | ||
c164855 | train | // GetSummary returns a table of precision, recall, true positive,
// false positive, and true negatives for each class for a given
// ConfusionMatrix | {
"resource": ""
} | ||
c164856 | train | // ShowConfusionMatrix return a human-readable version of a given
// ConfusionMatrix. | {
"resource": ""
} | ||
c164857 | train | // String returns a human-readable description of this AttributeSpec. | {
"resource": ""
} | ||
c164858 | train | // This file contains utility functions relating to Attributes and Attribute specifications.
// NonClassFloatAttributes returns all FloatAttributes which
// aren't designated as a class Attribute. | {
"resource": ""
} | ||
c164859 | train | // NonClassAttrs returns all Attributes which aren't designated as a
// class Attribute. | {
"resource": ""
} | ||
c164860 | train | // ResolveAttributes returns AttributeSpecs describing
// all of the Attributes. | {
"resource": ""
} | ||
c164861 | train | // ConvertRowToMat64 takes a list of Attributes, a FixedDataGrid
// and a row number, and returns the float values of that row
// in a mat.Dense format. | {
"resource": ""
} | ||
c164862 | train | // ConvertAllRowsToMat64 takes a list of Attributes and returns a vector
// of all rows in a mat.Dense format. | {
"resource": ""
} | ||
c164863 | train | // ParseCSVGetRowsFromReader returns the number of rows in a given reader. | {
"resource": ""
} | ||
c164864 | train | // ParseCSVEstimateFilePrecisionFromReader determines what the maximum number of
// digits occuring anywhere after the decimal point within the reader. | {
"resource": ""
} | ||
c164865 | train | // ParseCSVGetAttributesFromReader returns an ordered slice of appropriate-ly typed
// and named Attributes. | {
"resource": ""
} | ||
c164866 | train | // ParseCSVSniffAttributeNamesFromReader returns a slice containing the top row
// of a given reader with CSV-contents, or placeholders if hasHeaders is false. | {
"resource": ""
} | ||
c164867 | train | // ParseCSVSniffAttributeTypesFromReader 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": ""
} | ||
c164868 | train | // ParseCSVToInstancesFromReader reads the reader containing CSV and returns
// the read Instances. | {
"resource": ""
} | ||
c164869 | train | // ParseUtilsMatchAttrs tries to match the set of Attributes read from one file with
// those read from another, and writes the matching Attributes back to the original set. | {
"resource": ""
} | ||
c164870 | train | // ParseCSVToTemplatedInstancesFromReader reads the reader containing CSV and returns
// the read Instances, using another already read DenseInstances as a template. | {
"resource": ""
} | ||
c164871 | train | // ParseCSVToInstancesWithAttributeGroupsFromReader 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": ""
} | ||
c164872 | train | // NewChiMergeFilter creates a ChiMergeFilter with some helpful intialisations. | {
"resource": ""
} | ||
c164873 | train | // Transform returns the byte sequence after discretisation | {
"resource": ""
} | ||
c164874 | train | // maximum return the max heapNode in the heap. | {
"resource": ""
} | ||
c164875 | train | // extractMax remove the Max heapNode in the heap. | {
"resource": ""
} | ||
c164876 | train | // insert put a new heapNode into heap. | {
"resource": ""
} | ||
c164877 | train | //
// Utility functions
//
// computeGini computes the Gini impurity measure | {
"resource": ""
} | ||
c164878 | train | // computeGiniImpurity computes the average Gini index of a
// proposed split | {
"resource": ""
} | ||
c164879 | train | // String prints a human-readable summary of this thing. | {
"resource": ""
} | ||
c164880 | train | // Save sends the classification tree to an output file | {
"resource": ""
} | ||
c164881 | train | // Load reads from the classifier from an output file | {
"resource": ""
} | ||
c164882 | train | // LoadWithPrefix reads from the classifier from part of another model | {
"resource": ""
} | ||
c164883 | train | // Prune eliminates branches which hurt accuracy | {
"resource": ""
} | ||
c164884 | train | // Predict outputs a base.Instances containing predictions from this tree | {
"resource": ""
} | ||
c164885 | train | // NewID3DecisionTree returns a new ID3DecisionTree with the specified test-prune
// ratio and InformationGain as the rule generator.
// If the ratio is less than 0.001, the tree isn't pruned. | {
"resource": ""
} | ||
c164886 | train | // NewID3DecisionTreeFromRule returns a new ID3DecisionTree with the specified test-prun
// ratio and the given rule gnereator. | {
"resource": ""
} | ||
c164887 | train | // Fit builds the ID3 decision tree | {
"resource": ""
} | ||
c164888 | train | // Predict outputs predictions from the ID3 decision tree | {
"resource": ""
} | ||
c164889 | train | // NewBinaryConvertFilter creates a blank BinaryConvertFilter | {
"resource": ""
} | ||
c164890 | train | // Transform converts the given byte sequence using the old Attribute into the new
// byte sequence.
//
// If the old Attribute has a categorical value of at most two items, then a zero or
// non-zero byte sequence is returned.
//
// If the old Attribute has a categorical value of at most n-items, then a non-zero
// or... | {
"resource": ""
} | ||
c164891 | train | // SerializesInstancesToCSV converts a FixedDataGrid into a CSV file format. | {
"resource": ""
} | ||
c164892 | train | // SerializeInstancesToCSVStream outputs a FixedDataGrid into a CSV file format, via the io.Writer stream. | {
"resource": ""
} | ||
c164893 | train | // DeserializeInstances returns a DenseInstances using a given io.Reader. | {
"resource": ""
} | ||
c164894 | train | // SerializeInstances stores a FixedDataGrid into an efficient format to the given io.Writer stream. | {
"resource": ""
} | ||
c164895 | train | // NewMultiLinearSVC creates a new MultiLinearSVC using the OneVsAllModel.
// The loss and penalty arguments can be "l1" or "l2". Typical values are
// "l1" for the loss and "l2" for the penalty. The dual parameter controls
// whether the system solves the dual or primal SVM form, true should be used
// in most cases. ... | {
"resource": ""
} | ||
c164896 | train | // Predict issues predictions from the MultiLinearSVC. Each underlying LinearSVC is
// used to predict whether an instance takes on a class or some other class, and the
// model which definitively reports a given class is the one chosen. The result is
// undefined if all underlying models predict that the instance orig... | {
"resource": ""
} | ||
c164897 | train | // Number of Gaussians to fit in the mixture | {
"resource": ""
} | ||
c164898 | train | // Predict method - returns a ClusterMap of components and row ids | {
"resource": ""
} | ||
c164899 | train | // EM-specific functions
// Expectation step | {
"resource": ""
} |
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