This package provides methods to create fast and simple text classifiers, based on the same idea behind MicroTC.
The main idea is to perform a model selection among a large space of configurations, including preprocessing steps, weighting schemes, tokenizers (combinations), and classifiers. Moreover, TextClassification.jl
also includes support for different classifiers and fine-tune them in the search stage; additional support for weighthing shcmes, and a better support for distributed computing thanks to Julia. As the original implementation, this package is designed to be both domain and language independent.
- Popularity
- 1 Star
- Updated Last
- 1 Year Ago
- Started In
- November 2019
Required Packages
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Accessors
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Adapt
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ArgCheck
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ArrayInterface
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Atomix
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BangBang
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Baselet
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BitTwiddlingConvenienceFunctions
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CategoricalArrays
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CEnum
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ChainRulesCore
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ChangesOfVariables
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CloseOpenIntervals
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CommonSubexpressions
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CommonWorldInvalidations
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Compat
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CompositionsBase
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ConstructionBase
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ContextVariablesX
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CpuId
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CPUSummary
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Crayons
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DataAPI
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DataFrames
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DataStructures
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DataValueInterfaces
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DefineSingletons
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DelimitedFiles
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DiffResults
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DiffRules
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Distances
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Distributed
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DocStringExtensions
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FileIO
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FLoops
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FLoopsBase
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ForwardDiff
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GPUArrays
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HostCPUFeatures
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IfElse
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InitialValues
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InlineStrings
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Intersections
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InvertedFiles
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KNearestCenters
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LIBLINEAR
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MLUtils
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Parameters
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SearchModels
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SimilaritySearch
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SparseArrays
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StatsAPI
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StatsBase
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TextSearch
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