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microsoft / LightGBM

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Summary

mypy shows some issues in LightGBM's Python package.

mypy \
    --exclude='python-package/compile/|python-package/build' \
    --ignore-missing-imports \
    python-package/

18 errors in 4 files (click me)

python-package/lightgbm/compat.py:12: error: Name 'Series' already defined (possibly by an import)
python-package

List of dependencies that should be updated from time to time

6

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[python-package] type hints in python package

9

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catboost / catboost

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More concise error message with feature name, not only feature_idx

fingoldo commented Mar 24, 2022

Problem:

_catboost.pyx in _catboost._set_features_order_data_pd_data_frame()

_catboost.pyx in _catboost.get_cat_factor_bytes_representation()

CatBoostError: Invalid type for cat_feature[non-default value idx=1,feature_idx=336]=2.0 : cat_features must be integer or string, real number values and NaN values should be converted to string.

Could you also print a feature name, not o

GPU accelerated training not available during multitasking and model retraining

8

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susanli2016 / Machine-Learning-with-Python

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Python code for common Machine Learning Algorithms

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biolab / orange3

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💡 Orange: Interactive data analysis

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parrt / dtreeviz

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General Assembly's 2015 Data Science course in Washington, DC

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kk7nc / Text_Classification

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Text Classification Algorithms: A Survey

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edyoda / data-science-complete-tutorial

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For extensive instructor led learning

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alvinwan / neural-backed-decision-trees

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Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

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tensorflow / decision-forests

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A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

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dmitryikh / leaves

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mdabros / SharpLearning

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jmartinezheras / 2018-MachineLearning-Lectures-ESA

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Machine Learning Lectures at the European Space Agency (ESA) in 2018

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serengil / chefboost

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A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

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fukuball / fuku-ml

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Simple machine learning library / 簡單易用的機器學習套件

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Skylark0924 / Machine-Learning-is-ALL-You-Need

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Updated Mar 17, 2022
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jayshah19949596 / Machine-Learning-Models

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Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

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MATLAB

arnaldog12 / Machine_Learning

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nivu / ai_all_resources

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A curated list of Best Artificial Intelligence Resources

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dlab-berkeley / Machine-Learning-in-R

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CSS

RuleBasedIntegration / Rubi

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Include usage message of utility functions into the `Steps` display

halirutan commented Dec 12, 2018

Once #15 is implemented and we have a ::usage message for the integration-step condition function, this information should be included in the Steps display. I imagine for instance a tooltip when the user hovers over the green functions like IGtQ or GtQ

The implementation of this issue will require changed in [ShowStepFormatt

CynthiaKoopman / Network-Intrusion-Detection

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Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

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cerlymarco / linear-tree

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A python library to build Model Trees with Linear Models at the leaves.

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google / yggdrasil-decision-forests

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A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

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siboehm / lleaves

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Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.

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milaan9 / Machine_Learning_Algorithms_from_Scratch

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This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.

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rojaAchary / 30-Days-of-ML-Kaggle

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Machine learning beginner to Kaggle competitor in 30 days. Non-coders welcome. The program starts Monday, August 2, and lasts four weeks. It's designed for people who want to learn machine learning.

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Mayurji / MLWithPytorch

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Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

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Updated Dec 15, 2021
Python

decision-trees

Here are 1,995 public repositories matching this topic...

microsoft / LightGBM

[ci] warnings from mypy

Summary

List of dependencies that should be updated from time to time

[python-package] type hints in python package

catboost / catboost

More concise error message with feature name, not only feature_idx

Extend Callback Interface

GPU accelerated training not available during multitasking and model retraining

susanli2016 / Machine-Learning-with-Python

biolab / orange3

tirthajyoti / Machine-Learning-with-Python

parrt / dtreeviz

justmarkham / DAT8

kk7nc / Text_Classification

edyoda / data-science-complete-tutorial

alvinwan / neural-backed-decision-trees

tensorflow / decision-forests

RGF-team / rgf

dmitryikh / leaves

mdabros / SharpLearning

jmartinezheras / 2018-MachineLearning-Lectures-ESA

serengil / chefboost

fukuball / fuku-ml

Skylark0924 / Machine-Learning-is-ALL-You-Need

jayshah19949596 / Machine-Learning-Models

arnaldog12 / Machine_Learning

nivu / ai_all_resources

dlab-berkeley / Machine-Learning-in-R

RuleBasedIntegration / Rubi

Include usage message of utility functions into the `Steps` display

CynthiaKoopman / Network-Intrusion-Detection

cerlymarco / linear-tree

google / yggdrasil-decision-forests

siboehm / lleaves

milaan9 / Machine_Learning_Algorithms_from_Scratch

rojaAchary / 30-Days-of-ML-Kaggle

Mayurji / MLWithPytorch

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