nlp_primitives.DiversityScore#

class nlp_primitives.DiversityScore[source]#
Calculates the overall complexity of the text based on the total

number of words used in the text

Description:

Given a list of strings, calculates the total number of unique words divided by the total number of words in order to give the text a score from 0-1 that indicates how unique the words used in it are. This primitive only evaluates the ‘clean’ versions of strings, so ignoring cases, punctuation, and stopwords in its evaluation.

If a string is missing, return NaN

Examples

>>> diversity_score = DiversityScore()
>>> diversity_score(["hi hi hi", "hello its me", "hey what hey what", "a dog ate a basket"]).tolist()
[0.3333333333333333, 1.0, 0.5, 1.0]
__init__()#

Methods

__init__()

flatten_nested_input_types(input_types)

Flattens nested column schema inputs into a single list.

generate_name(base_feature_names)

generate_names(base_feature_names)

get_args_string()

get_arguments()

get_description(input_column_descriptions[, ...])

get_filepath(filename)

get_function()

Attributes

base_of

base_of_exclude

commutative

compatibility

Additional compatible libraries

default_value

Default value this feature returns if no data found.

description_template

input_types

woodwork.ColumnSchema types of inputs

max_stack_depth

name

Name of the primitive

number_output_features

Number of columns in feature matrix associated with this feature

return_type

ColumnSchema type of return

series_library

stack_on

stack_on_exclude

stack_on_self

uses_calc_time

uses_full_dataframe