Yet another library for hidden Markov models

learning-hmm alternatives and similar packages

Based on the "Algorithms" category

• build

  9.4 7.8 learning-hmm VS build

  Build systems a la carte

• arithmoi

  9.4 8.7 learning-hmm VS arithmoi

  Efficient basic number-theoretic functions. Primes, powers, integer logarithms.

• toysolver

  9.1 7.8 learning-hmm VS toysolver

  Assorted decision procedures for SAT, Max-SAT, PB, MIP, etc

• ersatz

  9.1 5.4 learning-hmm VS ersatz

  A monad for expressing SAT or QSAT problems using observable sharing.

• iproute

  8.8 3.3 learning-hmm VS iproute

  IP Routing Table

• primes

  8.3 0.0 learning-hmm VS primes

  Efficient, purely functional generation of prime numbers

• graphs

  8.2 3.8 learning-hmm VS graphs

  A simple monadic graph library

• funsat

  8.1 0.0 learning-hmm VS funsat

  A modern DPLL-style SAT solver

• HMM

  7.9 0.0 learning-hmm VS HMM

  A hidden markov model library

• imj-animation

  7.8 0.4 learning-hmm VS imj-animation

  Animation Framework

• union-find

  7.8 0.0 learning-hmm VS union-find

  Efficient union and equivalence testing of sets.

• aeson-diff

  7.8 2.4 learning-hmm VS aeson-diff

  Extract and apply patches to JSON documents.

• presburger

  7.4 0.4 learning-hmm VS presburger

  A decision procedure for quantifier-free linear arithmetic.

• text-metrics

  7.2 5.1 learning-hmm VS text-metrics

  Calculate various string metrics efficiently

• Adaptive

  7.1 0.0 learning-hmm VS Adaptive

  Library for incremental computing.

• edit-distance

  7.0 2.7 learning-hmm VS edit-distance

  Levenshtein and restricted Damerau-Levenshtein edit distances

• lca

  6.8 3.8 learning-hmm VS lca

  O(log n) persistent on-line lowest common ancestor calculation without preprocessing

• dtw

  6.5 0.0 learning-hmm VS dtw

  (Fast) Dynamic Time Warping

• treeviz

  6.3 0.0 learning-hmm VS treeviz

  Visualization of computation decomposition trees.

• ADPfusion

  6.2 0.0 learning-hmm VS ADPfusion

  Efficient, high-level dynamic programming.

• qchas

  6.2 0.3 learning-hmm VS qchas

  A library for implementing Quantum Algorithms

• incremental-sat-solver

  6.1 0.0 learning-hmm VS incremental-sat-solver

  Simple, Incremental SAT Solving as a Library

• ListTree

  5.3 0.0 learning-hmm VS ListTree

  Trees and monadic trees expressed as monadic lists where the underlying monad is a list

• cmaes

  5.0 0.0 L1 learning-hmm VS cmaes

  CMA-ES wrapper in Haskell

• search-algorithms

  5.0 0.0 learning-hmm VS search-algorithms

  Common graph search algorithms

• integer-logarithms

  4.8 3.6 learning-hmm VS integer-logarithms

  Integer logarithms.

• sgd

  4.8 7.0 learning-hmm VS sgd

  Stochastic gradient descent

• edit-distance-vector

  4.8 0.0 learning-hmm VS edit-distance-vector

  Calculate edit distances and edit scripts between vectors.

• binary-search

  4.6 0.0 learning-hmm VS binary-search

  Binary and exponential searches

• TrieMap

  4.3 0.0 learning-hmm VS TrieMap

  Automatic type inference of generalized tries with Template Haskell.

• union-find-array

  4.3 0.0 learning-hmm VS union-find-array

  union find data structure

• KMP

  4.3 0.7 learning-hmm VS KMP

  Knuth–Morris–Pratt string searching algorithm

• primesieve

  4.3 1.9 learning-hmm VS primesieve

  FFI bindings for the primesieve library.

• graph-generators

  4.1 0.0 learning-hmm VS graph-generators

  Functions for generating structured or random FGL graphs

• infinite-search

  4.1 0.0 learning-hmm VS infinite-search

  Exhaustively searchable infinite sets.

• DP

  4.1 0.0 learning-hmm VS DP

  Pragmatic framework for dynamic programming

• pathfinding

  3.8 0.0 learning-hmm VS pathfinding

  pathfinding in grid and graphs

• jps

  3.8 0.0 learning-hmm VS jps

  Jump point search for Haskell

• spacefill

  3.5 0.0 learning-hmm VS spacefill

  Generators for space-filling curves.

• nonlinear-optimization-ad

  3.5 0.0 learning-hmm VS nonlinear-optimization-ad

  Wrapper of nonlinear-optimization package for using with AD package

• edit-distance-linear

  3.1 7.1 learning-hmm VS edit-distance-linear

  Efficient implementation of the Levenshtein edit distance in linear memory.

• GraphSCC

  3.1 0.0 learning-hmm VS GraphSCC

  Tarjan's algorithm for computing the strongly connected components of a graph.

• fibonacci

  2.9 0.0 learning-hmm VS fibonacci

  Fast computation of Fibonacci numbers.

• twentyseven

  2.9 0.0 learning-hmm VS twentyseven

  Rubik's cube solver

• epanet-haskell

  2.9 0.0 L2 learning-hmm VS epanet-haskell

  Haskell binding for EPANET

• pell

  2.5 0.0 learning-hmm VS pell

  Package to solve the Generalized Pell Equation.

• stable-marriage

  2.5 0.0 learning-hmm VS stable-marriage

  algorithms around stable marriage

• dgim

  2.5 0.0 learning-hmm VS dgim

  Implementation of DGIM algorithm

• adp-multi

  2.1 0.0 learning-hmm VS adp-multi

  ADP for multiple context-free languages

• ADPfusionSet

  1.1 0.0 learning-hmm VS ADPfusionSet

  Dynamic programming for Set data structures.

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