FeatureNearest
FeatureNearest[{elem1,elem2,…},x]
gives the list of elemi to which x is nearest in a computed feature space.
FeatureNearest[{elem1v1,elem2v2,…},x]
gives the vi corresponding to the elemi to which x is nearest.
FeatureNearest[{elem1,elem2,…}{v1,v2,…},x]
gives the same result.
FeatureNearest[{elem1,elem2,…}prop,x]
gives the property prop for the elemi to which x is nearest.
FeatureNearest[data,{x1,x2,…}]
effectively gives {FeatureNearest[data,x1],FeatureNearest[data,x2],…}.
FeatureNearest[data,x,n]
gives the n nearest elemi to x.
FeatureNearest[data]
generates a NearestFunction[…] that can be applied repeatedly to different x.
Details and Options
- FeatureNearest can be used on many types of data, including numerical, textual, sounds and images, as well as combinations of these.
- Each elemi can be a single data element, a list of data elements, an association of data elements or a Dataset object. In FeatureNearest[data,…], data can be a Dataset object.
- In FeatureNearest[{elem1,elem2,…}prop,…], possible forms for prop include:
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"Element" the elemi found to be nearest "Index" the index i of the elemi found to be nearest "Distance" the distance to the nearest elemi {prop1,prop2,…} a list of multiple forms All an association giving element, index and distance - When several elements are returned, the nearest ones are given first.
- FeatureNearest is typically equivalent to using Nearest in the space created by FeatureExtract.
- The following options can be given:
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DistanceFunction Automatic the distance metric to use FeatureExtractor Identity how to extract features FeatureTypes Automatic feature types to assume for input data Method Automatic method to use RandomSeeding 1234 what seeding of pseudorandom generators should be done internally - Possible settings for RandomSeeding include:
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Automatic automatically reseed every time the function is called Inherited use externally seeded random numbers seed use an explicit integer or strings as a seed - Possible settings for Method include "Octree", "KDtree" and "Scan".
Examples
open allclose allBasic Examples (1)
Generate a nearest function using FeatureNearest:
Find the example in the dataset that is nearest to a new example:
Scope (4)
Generate a nearest function on a list of texts:
Find the nearest text for new examples:
Train a nearest function on a list of DateObject:
Find the two nearest elements from a new DateObject:
A string date can also be given:
Train a nearest function on a mixed-type dataset:
Find the nearest element of a new example:
Train a nearest function using the output property All:
Obtain the six nearest elements of a new example, along with position indices and distances:
Options (4)
DistanceFunction (1)
Generate a nearest function on a list of texts using the distance function EditDistance:
Find the nearest text for new examples:
When the distance function is specified, Nearest and FeatureNearest are equivalent:
FeatureExtractor (1)
Train a nearest function using FeatureExtractor to specify a preprocessing to the data:
FeatureTypes (1)
Train a nearest function using FeatureTypes to specify that "gender" is a nominal variable:
Applications (2)
Construct a dataset of dog images:
Train a nearest function using FeatureNearest:
Use this function on images that are not in the dataset:
Load the text of Alice in Wonderland:
Split the text into sentences:
Text
Wolfram Research (2017), FeatureNearest, Wolfram Language function, https://reference.wolfram.com/language/ref/FeatureNearest.html (updated 2017).
CMS
Wolfram Language. 2017. "FeatureNearest." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2017. https://reference.wolfram.com/language/ref/FeatureNearest.html.
APA
Wolfram Language. (2017). FeatureNearest. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/FeatureNearest.html