Cost-sensitive-Boosting-Tutorial

Classifier tools

Provides tools and methods for handling asymmetric classification problems in machine learning

Tutorial on cost-sensitive boosting and calibrated AdaMEC.

GitHub

26 stars
2 watching
16 forks
Language: Jupyter Notebook
last commit: over 9 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

RepositoryDescriptionStars
semiotic-ai/autoagoraAutomates cost modeling and optimization for indexers in blockchain networks using reinforcement learning and GraphQL APIs.11
jinlow/forustA package implementing a lightweight gradient boosted decision tree algorithm68
sjsingh91/ib-cnnA library implementing a learning algorithm for improving classification accuracy with incremental updates and ensemble methods using neural networks2
nv-tlabs/stealDevelops a method to create high-quality training data from noisy labels in semantic segmentation tasks.478
digitalglobe/mltoolsTools for building machine learning solutions on satellite imagery81
charliermarsh/online_boostingA suite of algorithms and weak learners for the online learning setting in machine learning65
funktor/stokastikA collection of algorithms and code snippets for machine learning blog development30
mmazeika/glcA method to train deep learning classifiers on noisy labels using a small set of trusted data86
harshakokel/kigbAn open-source software framework that integrates human advice into gradient boosting decision trees for improved performance in machine learning tasks.8
tqchen/xgboostAn optimized distributed gradient boosting library for machine learning572
google-research/noisystudentA semi-supervised learning method to improve the accuracy of machine learning models by using noisy teacher models and student models.755
usmanr149/classification-algorithmAn educational resource providing hands-on examples and exercises for learning classification algorithms using Python.2
ardanlabs/training-aiProvides training materials and tools for building machine learning applications72
hiroyuki-kasai/classifiertoolboxA collection of algorithms and tools for building classifiers in various machine learning applications.85
stanfordmlgroup/ngboostA Python library implementing a machine learning boosting framework with probabilistic prediction capabilities1,663