dataSDA (version 0.1.8)

interval_similarity: Similarity Measures for Interval Data

Description

Functions to compute similarity measures between interval-valued observations.

Usage

int_jaccard(x, var_name1, var_name2, ...)
int_dice(x, var_name1, var_name2, ...)
int_cosine(x, var_name1, var_name2, ...)
int_overlap_coefficient(x, var_name1, var_name2, ...)
int_tanimoto(x, var_name1, var_name2, ...)
int_similarity_matrix(x, method = "jaccard", ...)

Value

A numeric matrix or value

Arguments

x

interval-valued data with symbolic_tbl class.

var_name1

the first variable name or column location.

var_name2

the second variable name or column location.

...

additional parameters

method

similarity method for int_similarity_matrix: "jaccard", "dice", or "overlap".

Author

Han-Ming Wu

Details

These functions compute various similarity measures:

• int_jaccard: Jaccard similarity coefficient

• int_dice: Dice similarity coefficient

• int_cosine: Cosine similarity

• int_overlap_coefficient: Overlap coefficient

• int_tanimoto: Tanimoto coefficient (generalized Jaccard)

All similarity measures range from 0 (no similarity) to 1 (perfect similarity).

See Also

int_dist int_cor int_jaccard

Examples

data(mushroom.int)

# Jaccard similarity
int_jaccard(mushroom.int, "Pileus.Cap.Width", "Stipe.Length")

# Dice coefficient
int_dice(mushroom.int, 2, 3)

# Cosine similarity
int_cosine(mushroom.int, 
           var_name1 = c("Pileus.Cap.Width"), 
           var_name2 = c("Stipe.Length", "Stipe.Thickness"))

# Overlap coefficient
int_overlap_coefficient(mushroom.int, 2, 3:4)