Global

Methods

parse_ARFF(file_string) → {Dataset}

Parses an .ARFF file.
Parameters:
Name Type Description
file_string String The .ARFF file represented as a String
Source:
Returns:
The result as a Dataset object.
Type
Dataset

parse_CSV(name, file_string, delimiter, quotation_char) → {Dataset}

Parses a .csv file.
Parameters:
Name Type Description
name String A name for the dataset. e.g., anneal.
file_string String The .csv file represented as a String
delimiter Char what the file uses to separate values (usually ,)
quotation_char Char what the file uses to enclose quotation.
Source:
Returns:
The result as a Dataset object.
Type
Dataset

predict_attribute_type(attribute_values) → {String}

Given a set of attribute values, this function returns an intelligent guess of the attribute's type. Each attribute will either be 'numeric' or 'nominal'. This is done by predicting each values' type (numeric or nominal) then finally predicting the attribute's type as the most commonly predicted value type.
Parameters:
Name Type Description
attribute_values String | Array An array of all the values that appear at least once within the Records array of a Dataset object.
Source:
Returns:
"Numeric" if the attribute is predicted as numeric, "Categorical" if the attribute is predicted as categorical.
Type
String

values_from_csv_line(csv_line, delimiter, quotationChar) → {String|Array}

Given a line from a csv file, this function returns an array of all the values in that line.
Parameters:
Name Type Description
csv_line String The line from a csv file to get the values from.
delimiter char The delimiter used in the csv file.
quotationChar char The character used to denote quotation.
Source:
Returns:
An array of values represented as strings.
Type
String | Array