is an option for functions such as Classify that specifies how features should be extracted.
FeatureExtractor
is an option for functions such as Classify that specifies how features should be extracted.
Details
- Possible settings for FeatureExtractor include:
-
extractor apply the specified feature extractor method{extractor1,extractor2,…} apply the sequence of extractor methods in turnspecext apply extractor ext to data parts specified by spec{spec1ext1,spec2ext2,…} apply extractors exti to data parts specified by the speci
- Possible feature extractor methods include:
-
Automatic automatic extractionIdentity give data unchanged"ConformedData" conformed images, colors, dates, etc."NumericVector" numeric vector from any dataf applies function f to each example{extractor1,extractor2,…} use a sequence of extractors in turn
- Additional feature extractor methods can also be used for each data type.
- Numeric data:
-
"DiscretizedVector" discretized numerical data"DimensionReducedVector" reduced-dimension numeric vectors"MissingImputed" data with missing values imputed"StandardizedVector" numeric data processed with Standardize
- Nominal data:
-
"IndicatorVector" nominal data "one-hot encoded" with indicator vectors"IntegerVector" nominal data encoded with integers
- Text:
-
"LowerCasedText" text with each character lowercase"SegmentedCharacters" text segmented into characters"SegmentedWords" text segmented into words"SentenceVector" semantic embedding vector from a text"TFIDF" term frequency-inverse document frequency vector"WordVectors" semantic vectors sequence from a text (English only)
- Images:
-
"FaceFeatures" semantic vector from an image of a human face"ImageFeatures" semantic vector from an image"PixelVector" vector of pixel values from an image
- Audio objects:
-
"AudioFeatures" sequence of semantic vectors from an audio object"AudioFeatureVector" semantic vector from an audio object"LPC" audio linear prediction coefficients"MelSpectrogram" audio spectrogram with logarithmic frequency bins"MFCC" audio mel-frequency cepstral coefficient vectors sequence"SpeakerFeatures" sequence of semantic speaker vectors"SpeakerFeatureVector" semantic vector for a speaker"Spectrogram" audio spectrogram
- Video objects:
-
"VideoFeatures" sequence of semantic vectors from a video object"VideoFeatureVector" semantic vector from a video object
- Graphs:
-
"GraphFeatures" numeric vector summarizing graph properties
- Molecules:
-
"AtomPairs" Boolean vector from pairs of atoms and the path lengths between them"MoleculeExtendedConnectivity" Boolean vector from enumerated molecule subgraphs"MoleculeFeatures" numeric vector summarizing molecule properties"MoleculeTopologicalFeatures" Boolean vector from circular atom neighborhoods
- By default, FeatureExtractorIdentity .
- Typically, the value of FeatureExtractor is interpreted as a preprocessing step: it will not replace the other feature extractors used by the function.
- When the feature extractor method is not a FeatureExtractorFunction […] or a custom function, the feature extraction will be learned from the data.
- With the settings specext or {spec1ext1,…}, possible forms for spec and the speci include:
-
All all parts of each examplei i^(th) part of each example{i1,i2,…} parts i1, i2, … of each example"name" part with the specified name in each example{"name1","name2",…} parts with names "namei" in each example
- Parts not mentioned in spec or the speci are dropped for the purpose of extracting features.
- In functions such as Classify , Predict , DimensionReduction or ClusterClassify , FeatureExtractor"Minimal" indicates that the internal preprocessing should be as simple as possible.
Examples
open all close allBasic Examples (3)
Train a FeatureExtractorFunction on a simple dataset:
Use the feature extractor function as a preprocessing step in Classify :
Train a classifier using the extractor method "ImageFeatures" as a preprocessing step:
Classify a new image:
Generate a predictor function using FeatureExtractor to preprocess the data using a custom function:
Add the "StandardizedVector" method to the preprocessing pipeline:
Use the predictor on new data:
Scope (1)
Train a classifier on texts preprocessed by custom functions and an extractor method:
Related Guides
History
Introduced in 2016 (11.0) | Updated in 2018 (11.3) ▪ 2019 (12.0) ▪ 2020 (12.1) ▪ 2021 (12.3) ▪ 2025 (14.3)
Text
Wolfram Research (2016), FeatureExtractor, Wolfram Language function, https://reference.wolfram.com/language/ref/FeatureExtractor.html (updated 2025).
CMS
Wolfram Language. 2016. "FeatureExtractor." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2025. https://reference.wolfram.com/language/ref/FeatureExtractor.html.
APA
Wolfram Language. (2016). FeatureExtractor. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/FeatureExtractor.html
BibTeX
@misc{reference.wolfram_2025_featureextractor, author="Wolfram Research", title="{FeatureExtractor}", year="2025", howpublished="\url{https://reference.wolfram.com/language/ref/FeatureExtractor.html}", note=[Accessed: 16-November-2025]}
BibLaTeX
@online{reference.wolfram_2025_featureextractor, organization={Wolfram Research}, title={FeatureExtractor}, year={2025}, url={https://reference.wolfram.com/language/ref/FeatureExtractor.html}, note=[Accessed: 16-November-2025]}