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smote-oversampler

Here are 59 public repositories matching this topic...

Ava33343 / Risky_Business

Machine learning for credit card default. Precision-recalls are calculated due to imbalanced data. Confusion matrices and test statistics are compared with each other based on Logit over and under-sampling methods, decision tree, SVM, ensemble learning using Random Forest, Ada Boost and Gradient Boosting. Easy Ensemble AdaBoost classifier appear…

machine-learning svm scikit-learn ensemble-learning confusion-matrix adaboost decision-trees gradient-boosting statstics false-positive random-forest-classifier false-negative logisticsregression roc-curves recall-precision smoteenn smote-oversampler

Updated Jul 24, 2020
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mfriebel / lyrics_classifier

This project uses web scraping to download song text and uses Natural Language Processing (NLP) to predict an artist based a line of song text

python nlp regex bag-of-words tf-idf webscraping multinomial-naive-bayes beautifulsoup4 spacy-nlp smote-oversampler

Updated Mar 15, 2021
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ed12rivera / Credit_Risk_Analysis

Extract data provided by lending club, and transform it to be useable by predictive models.

logistic-regression accuracy-score balanced-random-forest smoteenn smote-oversampler cluster-centroids-undersampling easy-ensemble-classifier

Updated Apr 1, 2021
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cmmgw / Credit_Risk_Analysis

python numpy excel scikit-learn jupyter-notebook pandas collections supervised-machine-learning pathlib balanced-random-forest smote-oversampler imbalanced-learn naive-random-oversampler cluster-centroids-undersampling easy-ensemble-classifier smoteenn-combination

Updated Apr 10, 2021
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TrungLuong1194 / breast-cancer-classification

machine-learning deep-learning pytorch pca-analysis image-classification convolutional-neural-networks augmentation cancer-detection google-collab smote-oversampler

Updated Apr 23, 2021
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lidajav / Credit_Risk_Analysis

This project uses different techniques to train and evaluate models with unbalanced classes using credit card dataset to predict low-risk and high-risk credit cards.

confusion-matrix oversampling accuracy-score smoteenn smote-oversampler

Updated Apr 27, 2021
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ashley-green1 / Credit_Risk_Analysis

Data preparation, statistical reasoning and machine learning are used to solve an unbalanced classification problem. Different techniques are employed to train and evaluate models with unbalanced classes.

encoding machine-learning random-forest logistic-regression confusion-matrix supervised-machine-learning feature-importance random-forest-classifier sklearn-library binary-encoding train-test-using-sklearn train-test-split smoteenn smote-oversampler random-over-sampling cluster-centroids-undersampling easy-ensemble-classifier

Updated May 19, 2021
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Lsuantah / Credit_Risk_Analysis

The objective of this analysis was to use machine learning models to accurately predict credit risk.

python sklearn random-forest-classifier emsembling smoteenn smote-oversampler

Updated Jun 27, 2021
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nicoserrano / Credit_Risk_Analysis

Utilized several machine learning models to predict credit risk using Python's imbalanced-learn and scikit-learn libraries

machine-learning random-forest-classifier randomoversampler smoteenn smote-oversampler creditrisk-analysis clustercentroids easyensembleclassifier

Updated Sep 12, 2021
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toan01-uet / Solution-for-HackerEarth-Machine-Learning-challenge

HackerEarth Machine Learning challenge: Of Genomes And Genetics

data-science feature-engineering automl hackerearth-solutions target-encoding machinelearningchallenge imbalanced-classification mutilabelclassification smote-oversampler labelencoding

Updated Oct 6, 2021

ali-unlu / Travel-Customer-Churn-with-Oversampling

The aim of this post is to identify and visualize factors that contribute to customer churn of a travel company.

python eda churn-prediction classification-algorithm smote-oversampler

Updated Dec 13, 2021
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ali-unlu / Comparative-Principal-Component-Analysis

In this analysis, I will demonstrate how PCA works in different tasks and how much time and resources we save in our daily analysis.

pca-analysis pca logistic-regression k-means-clustering smote-oversampler

Updated Dec 20, 2021
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carzynsky / Analytics-and-Data-mining

etl naive-bayes-classifier pca logistic-regression mlp decision-tree svm-classifier ssis ssas random-forest-classifier knn-classifier rfe selectkbest smote-oversampler

Updated Jan 31, 2022
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ChriStingo / HeartDisease-Analysis-and-Prediction

Data analysis, visualization and prediction for the prevention of heart disease using ML models

data-science machine-learning random-forest machine-learning-algorithms data-visualization data-analysis knn roc-auc heart-disease-prediction smote-oversampler

Updated Feb 10, 2022
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xDiste / HeartDisease-Analysis-and-Prediction

Data analysis, visualization and prediction for the prevention of heart disease

data-science machine-learning random-forest machine-learning-algorithms prediction datavisualization dataanalysis medical-application roc-auc knn-classifier heartdieasesprediction smote-oversampler

Updated Feb 10, 2022
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tyedem / Risky_Business

Credit Risk Analysis utilizing imbalanced classification machine learning models

finance machine-learning risk-analysis random-forest scikit-learn classification ensemble-learning logistic-regression resampling smote-oversampler imbalanced-learn cluster-centroids-undersampling easy-ensemble-classifier smoteenn-combination

Updated Feb 10, 2022
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Sidessh / Multi-Class-Classification---License-Status-Prediction

Multi-class Classification - License Status Prediction

naive-bayes-classifier logistic-regression decision-trees imbalanced-data multiclass-classification knn-classification xgboost-classifier smote-oversampler

Updated Feb 14, 2022
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Credit_Risk_Analysis

ramya-ramamur / Credit_Risk_Analysis

Determine supervised machine learning model that can accurately predict credit risk using python's sklearn library. Python, Pandas, imbalanced-learn, skikit-learn

python random-forest scikit-learn ensemble-learning imbalanced-learning balanced-random-forest smote-oversampler naive-random-oversampler cluster-centroid-undersampling smoteenn-combination easyensembleclassifier

Updated Feb 25, 2022
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Sar-Go / Adult-Income-Prediction-AzureMLStudio

Future Ready Talent Project Submission.Using Azure ML Studio to predict the income of individuals, based on their age, race, education, residence city, etc. Used the adult census dataset

azure-machine-learning-studio boosted-decision-trees adult-census-income split-datasets smote-oversampler

Updated Feb 27, 2022

DougUOT / Credit_Risk_Analysis

We'll use Python to build and evaluate several machine learning models to predict credit risk. Being able to predict credit risk with machine learning algorithms can help banks and financial institutions predict anomalies, reduce risk cases, monitor portfolios, and provide recommendations on what to do in cases of fraud.

python machine-learning numpy scikit-learn jupyter-notebook pandas logistic-regression confusion-matrix classification-report centroids randomoversampler smoteenn smote-oversampler easyensembleclassifier balancedrandomforestclassifier

Updated Mar 5, 2022
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