generalized-additive-models
GLM.jl
| generalized-additive-models | GLM.jl | |
|---|---|---|
| 1 | 2 | |
| 13 | 576 | |
| - | 1.6% | |
| 7.0 | 5.0 | |
| 3 months ago | 6 days ago | |
| Python | Julia | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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generalized-additive-models
GLM.jl
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What is the Julia equivalent of Scikit-Learn?
Most things are broken up into different packages. For example: GLMs are here https://github.com/JuliaStats/GLM.jl
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Need help writing these two functions in Julia
You can use https://github.com/JuliaStats/GLM.jl
What are some alternatives?
pgmpy - Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
MLJ.jl - A Julia machine learning framework
pyhf - pure-Python HistFactory implementation with tensors and autodiff
DSGE.jl - Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
pandas-profiling - Create HTML profiling reports from pandas DataFrame objects [Moved to: https://github.com/ydataai/pandas-profiling]
RegressionTables.jl - Journal-style regression tables
scikit-learn - scikit-learn: machine learning in Python
ARCHModels.jl - A Julia package for estimating ARMA-GARCH models.
statsmodels - Statsmodels: statistical modeling and econometrics in Python
ScikitLearn.jl - Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
MixedModels.jl - A Julia package for fitting (statistical) mixed-effects models