Expand description
Natural Language Processing kernel approximations
This module provides kernel approximation methods specifically designed for NLP tasks, including text kernels, semantic features, syntactic approximations, and word embedding kernels.
Structs§
- Document
Kernel Approximation - Document kernel approximation for document-level features DocumentKernelApproximation
- Fitted
Document Kernel Approximation - FittedDocumentKernelApproximation
- Fitted
Semantic Kernel Approximation - FittedSemanticKernelApproximation
- Fitted
Syntactic Kernel Approximation - FittedSyntacticKernelApproximation
- Fitted
Text Kernel Approximation - FittedTextKernelApproximation
- Semantic
Kernel Approximation - Semantic kernel approximation using word embeddings and similarity measures SemanticKernelApproximation
- Syntactic
Kernel Approximation - Syntactic kernel approximation using parse trees and grammatical features SyntacticKernelApproximation
- Text
Kernel Approximation - Text kernel approximation using bag-of-words and n-gram features TextKernelApproximation
Enums§
- Aggregation
Method - AggregationMethod
- Similarity
Measure - SimilarityMeasure
- Tree
Kernel Type - TreeKernelType