The Wayback Machine - https://web.archive.org/web/20200907165425/https://github.com/topics/skewed-data

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skewed-data

Here are 8 public repositories matching this topic...

rbnx / skewboost

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Quantum ML for extremely imbalanced data

quantum-computing quantum-algorithms quantum-annealing skewed-data

Updated Aug 21, 2019
Python

dataengi / spark-challenges

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data engineering challenges and fun

spark data-engineering skewed-data

Updated May 29, 2020
Scala

Gelerion / spark-bin-packing-partitioner

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Fix data skew by packing into bins

trie tf-idf skewed-data

Updated Sep 23, 2019
Scala

fchamroukhi / MEteorits

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Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionS

clustering statistical-learning prediction artificial-intelligence statistical-inference neural-networks skew-t unsupervised-learning em-algorithm non-linear-regression t-distribution mixture-of-experts skewed-data robust-learning skew-normal

Updated Feb 13, 2020
R

charumakhijani / Advanced-House-Price-Prediction

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exploratory-data-analysis data-visualization kaggle-competition outlier-detection scaling house-price-prediction lasso-regression support-vector-regression kfold-cross-validation ensemble-models kernel-ridge-regression random-forest-regression missing-value-treatment skewed-data one-hot-encoding xgbregressor elastic-net-regression rmse-score lgbmregressor gradient-boosting-regression

Updated Jul 10, 2020
Jupyter Notebook

LJANGN / Predicting-Fraud-in-Financial-Payment-Services

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Trying to recogize and predict fraud in financial transactions is a good example of binary classification analysis. A transaction either is fraudulent, or it is genuine. What makes fraud detection especially challenging is the is the highly imbalanced distribution between positive (genuine) and negative (fraud) classes.

xgboost binary-classification fraud-detection skewed-data auprc

Updated Nov 4, 2018
Jupyter Notebook

Finding-Donors-for-Charity-using-Machine-Learning

sushantdhumak / Finding-Donors-for-Charity-using-Machine-Learning

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Machine Learning Nano-degree Project : To help a charity organization identify people most likely to donate to their cause

feature-selection supervised-learning accuracy confusion-matrix data-preprocessing data-normalization tuning-parameters gradient-boosting f1-score feature-importance gridsearchcv finding-donors naive-predictor skewed-data min-max-scaler fbeta-score

Updated Oct 19, 2019
Jupyter Notebook

gmgeorg / LambertW

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LambertW R package

normalization gaussianize normal-distribution skewed-data heavy-tailed heavy-tailed-distributions leptokurtosis gaussianize-data

Updated Jun 15, 2020
R

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