Publications by T. Moudiki
learningmachine: prediction intervals for conformalized Kernel ridge regression and Random Forest
I created R package learningmachine in the first place, in order to have a unified, object-oriented (using R6), interface for the machine learning algorithms I use the most on tabular data. This (work in progress) package is available on GitHub and the R-universe. There will certainly be a Python version in the future. This post shows how to use le...
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A plethora of datasets at your fingertips Part2: how many times do couples cheat on each other? Descriptive analytics, interpretability and prediction intervals using conformal prediction
Related To leave a comment for the author, please follow the link and comment on their blog: T. Moudiki's Webpage - R. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job. Want to share your content on R-bloggers? click ...
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Diffusion models in Python with esgtoolkit (Part2)
esgtoolkit version v1.1.0Disclaimer: I’ve used Quarto to generate this post, on a (Ubuntu Linux) machine that already had R installed.Install packagepip install esgtoolkit pip install jupyter import numpy as np import pandas as pd import seaborn as sns from esgtoolkit import simdiff, simshocks, esgplotbands from time import time # GBM print(" - G...
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Diffusion models in Python with esgtoolkit
A few weeks ago, on 2023-10-02, I announced esgtoolkit v1.0.0 for Python. Well, v1.0.0 for Python is more like a proof of concept as of today, as there isn’t an exact mapping with the R API so far. Next week, most likely in a v1.1.0 for both, the Python version will be aligned with the R version – as much as possible. For those who aren’t fam...
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Diffusion models in Python with esgtoolkit
A few weeks ago, on 2023-10-02, I announced esgtoolkit v1.0.0 for Python.Well, v1.0.0 for Python is more like a proof of concept as of today, as there isn’t an exact mapping with the R API so far. Next week, most likely in a v1.1.0 for both, the Python version will be aligned with the R version – as much as possible.For those who aren’t famil...
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Quasi-randomized nnetworks in Julia, Python and R
nnetsauce, a package for quasi-randomized supervised learning (classification and regression), is currently available for R and Python. For more details on nnetsauce, you can read these posts.I’ve always wanted to port nnetsauce to the Julia language. However, in the past few years, there was a little timing overhead (more precisely, a lag) when ...
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Diffusion models in ESGtoolkit + announcements
Contents 1 – news 2 – examples 1 – news Version 0.6.2 of ESGtoolkit is now available: on GitHub on R-universe It is now possible to use Hermite cubic spline and Smith-Wilson methods for yield curve interpolation. Starting with version 1.0.0, the next version, ESGtoolkit will be renamed as esgtoolkit or something similar, as I’m removin...
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A plethora of datasets at your fingertips
Starting with mlsauce’s next release (v0.9.0, for Python and R), you’ll be able to download a plethora of datasets for your statistical/machine learning experiments (this is a work in progress, it will done from a GitHub branch today). These datasets come from the R-universe, and you’ll be able to use them no matter whether you’re working w...
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A classifier that’s very accurate (and deep)
Version v0.15.0 of nnetsauce is now available on your favorite platforms: PyPI, conda and GitHub for Python; R universe and GitHub for R.The changes in this version are mostly related to Automated Machine learning (AutoML):lazy prediction for classification and regression: see this post for more details on the subject (and remember to use pip insta...
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mlsauce version 0.8.10: Statistical/Machine Learning with Python and R
This week, among other things, I’ve been working on updating mlsauce for both Python and R (that’s version 0.8.10 of the package).mlsauce is a package for Statistical/Machine Learning that contains in particular: AdaOpt, a probabilistic classifier which uses nearest neighbors to obtain predictions. Interestingly, with AdaOpt, one neighbor can s...
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