HROCH

High-Performance c++ symbolic regression library based on parallel local search

Zero hyperparameter tunning.
Accurate results in seconds or minutes, in contrast to slow GP-based methods.
Small models size.
Support for regression, classification and fuzzy math.
Support 32 and 64 bit floating point arithmetic.
Work with unprotected version of math operators (log, sqrt, division)
Speedup search by using feature importances computed from bbox model

Supported instructions
math	add, sub, mul, div, pdiv, inv, minv, sq2, pow, exp, log, sqrt, cbrt, aq
goniometric	sin, cos, tan, asin, acos, atan, sinh, cosh, tanh
other	nop, max, min, abs, floor, ceil, lt, gt, lte, gte
fuzzy	f_and, f_or, f_xor, f_impl, f_not, f_nand, f_nor, f_nxor, f_nimpl

Dependencies

AVX2 instructions set(all modern CPU support this)
numpy
sklearn
scipy

Installation

pip install HROCH

Usage

Symbolic_Regression_Demo.ipynb

Documentation

from HROCH import SymbolicRegressor

reg = SymbolicRegressor(num_threads=8, time_limit=60.0, problem='math', precision='f64')
reg.fit(X_train, y_train)
yp = reg.predict(X_test)

Changelog

v1.4

Sklearn compatibility
Classificators:
- NonlinearLogisticRegressor for a binary classification
- SymbolicClassifier for multiclass classification
- FuzzyRegressor for a special binary classification
Xi corelation used for filter unrelated features

v1.3

Public c++ sources
Commanline interface changed to cpython
Support for classification score logloss and accuracy
Support for final transformations:
- ordinal regression
- logistic function
- clipping
Acess to equations from all paralel hillclimbers
User defined constants

v1.2

Features probability as input parameter
Custom instructions set
Parallel hilclimbing parameters

v1.1

Improved late acceptance hillclimbing

v1.0

First release

SRBench

Release files for HROCH 1.4.12

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for HROCH 1.4.12
File	Size	Uploaded
hroch-1.4.12.tar.gz	445.9 kB	Aug 31, 2024	Details

Built distribution (wheel)

Table of built distributions (wheels) for HROCH 1.4.12
File	Interpreter	ABI	Platform	Reset
HROCH-1.4.12-py3-none-any.whl 454.5 kB Aug 31, 2024	Python 3	none	any	Details

Total release size: 900.4 kB

Release files / hroch-1.4.12.tar.gz

Download URL	hroch-1.4.12.tar.gz
Size	445.9 kB
Tags	Source
SHA-256 checksum How to use checksums	`a7e934bdb4df9314df3328d15ae48552ee8ffc4aa7ec2006e6f7f49300c38f74`
BLAKE2b-256 checksum How to use checksums	`a084d2b2983718f966a6420885c5e241032361010460cba865fcea0da2dc7164`
Upload date	Aug 31, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.1.0 CPython/3.12.5`

Release files / HROCH-1.4.12-py3-none-any.whl

Download URL	HROCH-1.4.12-py3-none-any.whl
Size	454.5 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`f6d3fe40804908bc6535779c82a473e96944c4c0c6e1339bea344763b5f88f68`
BLAKE2b-256 checksum How to use checksums	`ba4b70d399b1cb6301a93a1892e563b392fb64f70b667cc4d7562187051395ca`
Upload date	Aug 31, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.1.0 CPython/3.12.5`