Synthetic Minority Over-Sampling Technique for Regression
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Feb 7, 2024 - Python
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over-sampling
Here are 18 public repositories matching this topic...
Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Frauds is less than 0.00005 thus, simply applying Classification Algorithm may result in Overfitting
finance machine-learning query deep-learning data-visualization data-analytics classification data-analysis sampling confusion-matrix large-dataset classification-report anamoly-detection auprc under-sampling over-sampling
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May 23, 2019 - Jupyter Notebook
RCSMOTE: Range-Controlled Synthetic Minority Over-sampling Technique for handling the class imbalance problem
smote over-sampling imbalanced-classification smote-sampling imbalanced-datasets class-imbalance-problem
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Aug 31, 2024
Predicting students admission with Logistic Regression, Decision Tree, SVM (SVC) and Random Forest
machine-learning random-forest machine-learning-algorithms logistic-regression resampling decision-tree prediction-model svc kfold-cross-validation machine-learning-projects over-sampling performance-measurements
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May 1, 2023 - Jupyter Notebook
Trained and evaluated two supervised machine learning models using original and resampled data to identify 'healthy loan' and 'high risk loan' applicants from financial disclosures.
numpy reporting sklearn pandas logistic-regression classification-report supervised-machine-learning pathlib over-sampling train-test-split
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Jun 7, 2023 - Jupyter Notebook
Multivariate Normal Distribution Based Over-Sampling for Numerical and Categorical Features
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Jan 6, 2020 - Jupyter Notebook
In this project, data analytics is used to analyze customer-level data of a leading telecom firm, build predictive models to identify customers at high risk of churn, and identify the main indicators of churn. The project focuses on a four-month window, wherein the first two months are the ‘good’ phase, the third month is the ‘action’ phase, whi…
machine-learning statistics telecom data-analytics xgboost pca classification logistic-regression data-manipulation feature-engineering class-imbalance data-cleaning hyperparameter-tuning evaluation-metrics model-evaluation smote model-building random-forest-classifier rfe over-sampling
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Jul 9, 2021 - Jupyter Notebook
Genre Identification task along with Text Analytics with Multi-Class and Imbalanced Learning on Gutenberg Corpus
python machine-learning neural-network naive-bayes-classifier logistic-regression gutenberg text-analytics decision-tree-classifier imbalanced-data multiclass-classification imbalanced-learning complement-navie-bayes random-forest-classifier text-retrieval svm-rbf over-sampling
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Nov 24, 2020 - HTML
Football Positions: A Multi-class Classification Problem
machine-learning feature-engineering grid-search lime multi-class-classification shannon-entropy cost-sensitive-classification shap model-interpretability over-sampling
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Sep 4, 2022 - Jupyter Notebook
Credit Card Fraud detection based on anonymized data using multiple classification algorithms
python random-forest pandas credit-card-fraud xgboost classification logistic-regression decision-trees class-imbalance smote skewness under-sampling over-sampling
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Jan 28, 2021 - Jupyter Notebook
Predicts the qualified employee for promotion using Classification
random hr logistic-regression decision-tree smote knn-classification classifcation ensemble-methods imbalance over-sampling gaussiannb experimenting-stacking
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Dec 5, 2021 - Jupyter Notebook
Multivariate Normal Distribution based Oversampling
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Mar 18, 2019 - Jupyter Notebook
Use random forest, gradient boosting, neural network, with SMOTE-ENN and random over-sampling
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Feb 9, 2023 - Jupyter Notebook
The aim of this project is to determine which classification technique produces the best results when applied to the task of determining credit riskiness.
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Aug 14, 2020 - Jupyter Notebook
Imbalanced data commonly exist in real world, especially in anomaly-detection tasks. Handling imbalanced data is important to the tasks, otherwise the predictions are biased towards the majority class. RandomOverSampler, SMOTE, and ADASYN are useful oversampling tools to fabricate data for minority classes and make the dataset balanced.
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Aug 29, 2023 - Jupyter Notebook
Kaggle Competition: Predictions of West Nile Virus outbreaks in the City of Chicago.
time-series exploratory-data-analysis kaggle-competition cost-benefit-analysis classification-models over-sampling
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Jan 31, 2021 - Jupyter Notebook
Supervised Machine Learning and Credit Risk
machine-learning scikit-learn machine-learning-algorithms scikitlearn-machine-learning ada-boost-classifier precision-recall imbalance-learning under-sampling over-sampling balanced-random-forest smote-oversampler naive-random-oversampler cluster-centroids-undersampling easy-ensemble-classifier
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Feb 4, 2023 - Jupyter Notebook
Repo contains scripts to perform data analysis on structure data. It also provides a comparison of various ML algorithms at different stages of data preparation.
data-science machine-learning-algorithms data-analysis data-preparation binary-classification cost-sensitive-learning under-sampling over-sampling
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Dec 2, 2020 - Jupyter Notebook
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