Ecosyste.ms: Repos

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GitHub topics: imblearn

Repositories

viniciusds2020/ml_balaceamento_allknn

Este repositório contém um código de Machine Learning que utiliza o algoritmo AllKNN do pacote imblearn para realizar o balanceamento de dados.

Language: Jupyter Notebook - Size: 5.86 KB - Last synced: 4 days ago - Pushed: 4 days ago - Stars: 0 - Forks: 0

shinho123/23.11.10-1st-Korean-Society-of-Industrial-Engineers

2023년 11월 대한산업공학회(UNIST) : 다중 역할 경험을 고려한 게임 유저 이탈 예측: 롤 게임을 중심으로, 1저자

Language: Jupyter Notebook - Size: 45 MB - Last synced: 7 days ago - Pushed: 7 days ago - Stars: 1 - Forks: 0

mathewsrc/AWS-Machine-Learning-Engineer-Capstone

This project aims to train three classification models (LogisticRegression, DecisionTree and RandomForest) using AWS SageMaker to classify customer churn from a database obtained from kaggle.com.

Language: Jupyter Notebook - Size: 10.5 MB - Last synced: about 1 month ago - Pushed: about 1 year ago - Stars: 0 - Forks: 1

Vergosss/Decision_Theory_2023_2024_Project

Language: Python - Size: 494 KB - Last synced: about 1 month ago - Pushed: about 2 months ago - Stars: 1 - Forks: 0

christopher-w-murphy/Notes-on-Decision-Trees-and-Random-Forests

These are my notes for the interview prep workshop I led on Random Forests

Language: Jupyter Notebook - Size: 2.21 MB - Last synced: about 1 month ago - Pushed: over 5 years ago - Stars: 0 - Forks: 3

jpcadena/cancer-classification

Breast cancer classification project.

Language: Python - Size: 625 KB - Last synced: about 2 months ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

pratik-choudhari/Intent-classification-using-python

Imbalanced Intent classification model with deployment

Language: JavaScript - Size: 6.53 MB - Last synced: about 2 months ago - Pushed: over 3 years ago - Stars: 4 - Forks: 1

LaurentVeyssier/Starbucks_case_study_Udacity_Data_Science

Case study from UDACITY Data Scientist Nanodegree

Language: Jupyter Notebook - Size: 1.75 MB - Last synced: 2 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

apethani21/aus-rain-prediction

Binary classification project on trying to predict whether or not it will rain the next day using weather features, for various locations across Australia.

Language: Jupyter Notebook - Size: 24.6 MB - Last synced: 4 months ago - Pushed: about 3 years ago - Stars: 0 - Forks: 0

alaa-aleryani/Credit_Risk_Classification

We used various techniques to train and evaluate a model based on loan risk. We used a dataset of historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.

Language: Jupyter Notebook - Size: 528 KB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 0 - Forks: 0

Shipra-09/Project-Vehicle-Insurance

This Github repository contains cross selling of health insurance customers on vehicle insurance product. We have to predict whether a customer would be interested in Vehicle Insurance or not by building a ML model. Exploring Insights/Inferences by performing EDA on the given project data. Finding the high accuracy

Language: Jupyter Notebook - Size: 10.1 MB - Last synced: 4 months ago - Pushed: 5 months ago - Stars: 0 - Forks: 0

saurabhwankhede022/Data-Science-With-Project-s

Data Science With Project's

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saikrishnabudi/Random-Forests

Use Random Forest to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.

Language: Jupyter Notebook - Size: 4.74 MB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 0 - Forks: 0

Dhrumil-Zion/Sentiments-Prediction-Using-NLP

Predicting customer sentiments from feedbacks for amazon. While exploring NLP and its fundamentals, I have executed many data preprocessing techniques. In this repository, I have implemented a bag of words using CountVectorizer class from sklearn. I have trained this vector using the LogisticRegression algorithm which gives approx 93% accuracy. I have found out the top 20 positive and negative feedback words from thousands how feedbacks. Also after processing this much I have automated the whole process with one function so that it can be used as generic for many machine learning algorithms. I have also tested another algorithm called DummyClassifier which gives an accuracy of around 84%. After that, I have executed the famous algorithm which is TF-IDF for NLP. I have combined TF-IDF with LogisticRegression which gives almost 93% accuracy but deep insights. Also, while working with data has solved the problem of imbalanced data through RandomOverSampler class from imblearn library.

Language: Jupyter Notebook - Size: 316 KB - Last synced: 5 months ago - Pushed: about 3 years ago - Stars: 0 - Forks: 0

nickjlupu/Credit-Risk

Supervised scikit-learn machine learning models using several sampling techniques.

Language: Jupyter Notebook - Size: 18.4 MB - Last synced: 5 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

alessandrosocc/Machine-Learning-Project-2022

Final project of the Machine Learning course at the University of Cagliari in 2022. Analysis of a dataset, use of Machine Learning techniques with Oversampling and Undersampling techniques. Final report with the results obtained.

Language: Python - Size: 1.4 MB - Last synced: 4 months ago - Pushed: 5 months ago - Stars: 1 - Forks: 0

xinguanca/MLproject_creditcardfraud

My first machine learning project.

Language: Jupyter Notebook - Size: 33.2 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

SzymonWilczewski/bank-client-classification-ai

Project for "Computational intelligence" course

Language: Jupyter Notebook - Size: 690 KB - Last synced: 5 months ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

egorumaev/2023-cirrhosis-outcomes

Прогнозирование исхода лечения пациентов с циррозом печени

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egorumaev/2023-ods-turnstiles

Идентификация посетителя в зависимости от характерного времени его прохода на территорию организации

Language: Jupyter Notebook - Size: 1.98 MB - Last synced: 6 months ago - Pushed: 6 months ago - Stars: 0 - Forks: 0

Emeraldugbeyide93/Undersampling-and-Oversampling-techniques-for-imbalanced-datasets

Beginner friendly project focusing on dataset imbalances using the oversampling and under sampling techniques

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kirankirank/imbalenced-data

imbalanced data

Language: Python - Size: 7.81 KB - Last synced: 6 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

pratiksha2712/Customer-Churn-Analysis-and-Prediction

Data analysis and ML Modelling

Language: Jupyter Notebook - Size: 1.14 MB - Last synced: 7 months ago - Pushed: 11 months ago - Stars: 0 - Forks: 0

sharmaroshan/Fraud-Detection-in-Insurace-Claims

This is a very Important part of Data Science Case Study because Detecting Frauds and Analyzing their Behaviours and finding reasons behind them is one of the prime responsibilities of a Data Scientist. This is the Branch which comes under Anamoly Detection.

Language: Jupyter Notebook - Size: 2.23 MB - Last synced: 8 months ago - Pushed: almost 5 years ago - Stars: 7 - Forks: 3

GenTaylor/Traffic-Accident-Analysis

Traffic Accident Analysis using python machine learning

Language: Jupyter Notebook - Size: 36.4 MB - Last synced: 8 months ago - Pushed: about 3 years ago - Stars: 15 - Forks: 9

alecngo/cervical-cancer-project

Deploy SVM, Random Forest, and Streamlit Package to make a web app to early detect Cervical Cancer

Language: Jupyter Notebook - Size: 5.46 MB - Last synced: 8 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

pranshu1921/Personalised-Cancer-Diagnosis

Predict the effect of genetic mutations in cancer tumors and classify them based on text clinical literature.

Language: Jupyter Notebook - Size: 1.37 MB - Last synced: 8 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

ats-tandjoeng7/Credit_Risk_Analysis

Application of various supervised Machine Learning techniques to solve a real-world case study.

Language: Jupyter Notebook - Size: 18.5 MB - Last synced: 9 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

jianninapinto/Bandersnatch Fork of BloomTech-Labs/BandersnatchStarter

This project implements a machine learning model using Random Forest, XGBoost, and Support Vector Machines algorithms with oversampling and undersampling techniques to handle imbalanced classes for classification tasks in the context of predicting the rarity of monsters.

Language: Jupyter Notebook - Size: 581 KB - Last synced: 10 months ago - Pushed: 10 months ago - Stars: 0 - Forks: 0

earlyann/Stock_predictions

Using and comparing Support Vector machine, Random Branch Forest and Easy Ensemble algorithms to predict if a stock will have a positive or negative annual return.

Language: Jupyter Notebook - Size: 1020 KB - Last synced: 10 months ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

TrilokiDA/Credit-Card-Fraud-Detection

Synthetic Financial Datasets For Fraud Detection

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cp-PYFOREST/PYFOREST-ML

Utilizing machine learning to examine deforestation rates in the undeveloped region of Paraguay's Chaco

Language: Jupyter Notebook - Size: 16.2 MB - Last synced: 4 months ago - Pushed: 12 months ago - Stars: 1 - Forks: 2

suyinwb/Credit_Risk_Analysis

Using the credit card credit dataset from LendingClub, a peer-to-peer lending services company, you’ll oversample the data using the RandomOverSampler and SMOTE algorithms, and undersample the data using the ClusterCentroids algorithm. Then, you’ll use a combinatorial approach of over- and undersampling using the SMOTEENN algorithm.

Language: Jupyter Notebook - Size: 720 KB - Last synced: 11 months ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

nnilayy/Classification-Notebook

Data Science Classification General Notebook

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Priyanshusinhaa/CreditCardFraudDetection

Notebook represents the process of fraud detection using past data.

Language: Jupyter Notebook - Size: 372 KB - Last synced: 12 months ago - Pushed: 12 months ago - Stars: 0 - Forks: 0

MirrasHue/Intro-to-AI

An assignment from my Introduction to Artificial Intelligence course, in which we had to treat the datasets, train some models for classification and adjust their parameters

Language: Jupyter Notebook - Size: 0 Bytes - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

rewatevijaykumar/sensor-fault-detection

The Air Pressure System (APS) is crucial for heavy duty vehicles, utilizing compressed air to break pads and slow down the vehicle. The aim of this binary classification project is to minimize unnecessary repair costs by identifying component failure in APS, using Python, FastAPI, Machine Learning Algorithm, Docker and MongoDB.

Language: Jupyter Notebook - Size: 12.1 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

Sajid030/fraud_detection

In this repository I have trained my machine learning model to detect whether there was fraud or not in your online transaction.

Language: Jupyter Notebook - Size: 7.47 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

vsdcarneiro/Projeto-Integrado-PUC

Trabalho de Conclusão de Curso apresentado ao Curso de Especialização em Inteligência Artificial e Aprendizado de Máquina, como requisito parcial à obtenção do título de Especialista.

Language: Jupyter Notebook - Size: 20.3 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

shanuhalli/Assignment-Random-Forest

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binaryvexjuiit/Detecting-Facial-Diseases-Through-Neural-Networks

Facial skin disease detection using Neural Networks

Language: Python - Size: 367 KB - Last synced: 12 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

ChaitanyaC22/Fraud_Analytics_Credit_Card_Fraud_Detection

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

Language: Jupyter Notebook - Size: 67.3 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 1

shayleaschreurs/Machine-Learning-Trading-Bot

Our goal was to create a ML bot that analyzes real time trading data to determine the most opportune times buy and sell stock

Language: Jupyter Notebook - Size: 9.07 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

guilhermedom/pyspark-horsepower-multilinear-regression

PySpark for multiple linear regression on car horsepower using SMOTE for data augmentation.

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digvijaytaunk/aps-fault-detection-with-deployment

Language: Jupyter Notebook - Size: 20.6 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

prohogiy90/ds-model-of-the-behavior-of-the-SberAvtopodpiska-customers

This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"

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ngfelixxx/Bank-Account-Machine-Learning-Model

Performing Feature Engineering, Hyperparameter Tuning , and Classification Algorithms.

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schatzederwelt/toxic_comments_detection

Автоматическое выявление токсичных комментариев

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shayleaschreurs/Supervised_Learning_Regression_Model

Module 12 - Using the imblearn , I'll use a logistic regression model to compare 2 versions of a dataset. First, I’ll use the original data. Next, I’ll resample the data by using RandomOverSampler. In both cases, I’ll get the count of the target classes, train a logistic regression classifier, calculate the balanced accuracy score, generate a con

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