GitHub topics: classification-report

Repositories

marcogdepinto/emotion-classification-from-audio-files

Understanding emotions from audio files using neural networks and multiple datasets.

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thieu1995/permetrics

Artificial intelligence (AI, ML, DL) performance metrics implemented in Python

Language: Python - Size: 2.36 MB - Last synced at: 5 days ago - Pushed at: 9 months ago - Stars: 76 - Forks: 18

Aliakbar-omidi/Sentiment-Review

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Mryadav02/Credit_score_prediction

Watch me build a website which can predict the credit score , based on inputs given

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mehtadigisha/Iris-Flower-Classification

Iris Flower Classification

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Aliakbar-omidi/Brain-Tumor-Detection

This project focuses on detecting and classifying brain tumors (NonDemented, Very Mild Demented, Mild Demented, Moderate Demented)

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sushant1827/Machine-Learning-for-Predictive-Maintenance

Demonstrate the application of machine learning on a real-world predictive maintenance dataset, using measurements from actual industrial equipment.

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venkat-0706/Titanic-Survival-Prediction

A machine learning project predicting Titanic passenger survival using data preprocessing, feature engineering, and model optimization with Logistic Regression, Random Forest, and XGBoost.

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BatthulaVinay/phone-usage-analysis

This project analyzes phone usage patterns in India and predicts the primary use of mobile devices based on various features. The notebook covers data preprocessing, exploratory data analysis (EDA), and model training using multiple classification algorithms.

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anushkundu/Churn-Prediction

Telecom Customer Churn Prediction Using Machine Learning!

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aaaastark/Intrusion-Detection-System-MQTT-Enabled-IoT

Intrusion Detection System for MQTT Enabled IoT.

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sushant1827/Fashion-Clothing-Classification

Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images

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jeffreywijaya100/ecommerce-product-textmining

Pemodelan klasifikasi menggunakan data product dari sebuah ecommerce dengan ketentuan yang diberikan

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OlisehOkiah/Online-Payment-Fraud

Build a machine learning model to detect fraudulent online payment transactions with high accuracy. The project includes data preprocessing, SMOTE for class imbalance correction, and deployment using Streamlit for real-time predictions.

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maheera421/Heart-Disease-Diagnosis-Model

A machine learning project designed to predict the likelihood of heart disease based on a set of health indicators.

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harmanveer-2546/Ad-Click-Prediction-Analysis-and-Insights

To predict whether a user will click on ad or not.

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varmatilak22/Credit_Score_Prediction

This project predicts credit scores ('Good', 'Standard', 'Poor') using a streamlined ML pipeline. It includes data extraction, cleaning, and preprocessing. Key techniques are Mutual Information for feature selection, PCA for dimensionality reduction, and XGBoost for accurate and efficient model training, ensuring reliable and robust predictions.

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HirudikaAnupama/Email-Spam-Detection-Logistic-Regression

This model can predict whether an email is spam or not. The logistic regression machine learning algorithm is used to train this model.

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blleshi/Credit_Risk_Classification

Credit Risk Classification

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harmanveer-2546/Student-performance-in-exam

Student performance analysis and prediction using datasets has become an essential component of modern education systems. With the increasing availability of data on student, schools and universities are using advanced analytics and machine learning algorithms to gain insights into student performance and predict future outcomes.

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maridda/nerval

Python framework to evaluate Named Entity Recognition (NER) models. Creates entity-level confusion matrix and classification report.

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chinmoyt03/Deep-Learning-Based-Diabetes-Risk-Analysis

Data Science Project: Comparing 3 Deep Learning Methods (CNN, LSTM, and Transfer Learning).

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Saba-Gul/-PyCaret-Streamline-Your-Machine-Learning-Workflow

PyCaret: Simplifying machine learning workflows with a low-code, open-source Python library.

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Vishakha-33/CreditCardFraudDetection

This repository features code for a fraud detection model achieving 100% accuracy in identifying fraudulent credit card transactions. Utilizing transaction data from Jan 2019 to Dec 2020, the model employs RandomForestClassifier, assessing features like credit card numbers, transaction amounts, and merchant information.

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DylanMontoya/MeetupPythonMedellin

I spoke about Natural Language Processing (NLP) for sentiment analysis in tweets. By community Python Medellin & Machine Learning Colombia

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AISWARYA-NANDAKUMAR/Prediction-of-Breast-Cancer-from-Histopathological-Images

Different networks, 2D CNN, 1X1 filter, VGG16 and Inception network is used for predicting breast cancer from histopathological images. Performance of different models are compared and found out that InceptionNet performed the best.

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Aalaa4444/Garbage_Classification

CNN model to classify garbage

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jodiambra/Sure-Tomorrow-Insurance-Benefits-Predictions

We conduct cluster analysis on customers and machine learning to predict if a customer will receive insurance benefits.

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pkiage/tool-credit-risk-modelling

Tool demonstrating building credit risk models

Language: Python - Size: 487 KB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 3

MuhammadUsmanTipu/Classification-IBM-Project

The dataset is about past loans. The loan_train.csv data set includes details of 346 customers whose loans are already paid off or defaulted.

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Robyn2024/Credit_Risk_Classification

I'll use various techniques to train and evaluate a model based on loan risk. I will use 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.

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fischlerben/Machine-Learning-Credit-Risk

Machine-Learning project that uses a variety of credit-related risk factors to predict a potential client's credit risk. Machine Learning models include Logistic Regression, Balanced Random Forest and EasyEnsemble, and a variety of re-sampling techniques are used (Oversampling/SMOTE, Undersampling/Cluster Centroids, and SMOTEENN) to re-sample the data. Evaluation metrics like the accuracy score, classification report and confusion matrix are generated to compare models and determine which suits this particular set of data best.

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RJBarker/credit-risk-classification

Create a Logistic Regression model to predict the credit risk of customers to a lending company. Use historical data and train the model before making predictions of test data. Lastly write an analysis report on the models created.

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Abanobbb/Breast-Cancer-Classification

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Ramyadeveloper59/Water-Quality-Prediction-by-using-Machine-Learning.

The main purpose of our proposed method is used to predict the quality of water by using Machine Learning algorithm.

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ashishyadav24092000/OptimumThreshold_ROC

Here we will be firstly analysing the how different threshold values effect the area under the Curve in a Receiver Operating charcteristic(ROC) curve. And at last we will show how to define a function in python to calculate the most optimal threshold value for the logistic Regression.

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asood0113/Logistic-regression-and-data-visualisation

Building a model to classify student grade based on various factors and conducting exploratory data analysis

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vaitybharati/P36.-Supervised-ML---Decision-Tree---C5.0-Entropy-Iris-Flower-

Supervised-ML-Decision-Tree-C5.0-Entropy-Iris-Flower-Using Entropy Criteria - Classification Model. Import Libraries and data set, EDA, Apply Label Encoding, Model Building - Building/Training Decision Tree Classifier (C5.0) using Entropy Criteria. Validation and Testing Decision Tree Classifier (C5.0) Model

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sharmaroshan/Fraud-Detection-in-Online-Transactions

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

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sahilichake/Indian-Crime-Data-Analysis-Forecasting

Conducted data analysis, statistical analysis, and data visualization on an Indian crime dataset. Applied various machine learning algorithms to gain insights from the data. Utilized Time-Series models for prediction and forecasting based on the crime data analysis.

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spChalk/Vaccine-Sentiment-Classifier

:syringe: Vaccine Sentiment Classifier is a deep learning classifier trained on real world twitter data, that distinguishes 3 types of tweets: Neutral, Anti-vax & Pro-vax.

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moggirain/SNL_discharge_prediction

predict where the patient will be discharged to before surgery

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AnoopER1999/Bank-Personal-Loan-Modelling----Logistic-Regression

Objective: The department wants to build a model that will help them identify the potential customers who have a higher probability of purchasing the loan. This will increase the success ratio while at the same time reducing the cost of the campaign.

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jianninapinto/Default-Loan-Predictor

Trained a classifier by using labeled data and SMOTE techniques to predict if a borrower will default on a loan. The machine learning model is intended to be used as a reference tool to help investors make informed decisions about lending to potential borrowers based on their ability to repay. The purpose is to lower risk and maximize profit.

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imane-ayouni/Breast-Cancer-Detection-from-Ultrasound-pictures-using-CNN

CNN to classify ultrasounds of cancerous and non cancerous cells

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S-CHAN11/Insurance-Claim-Prediction

In this project, I use 3 machine learning models (CART, Random Forest and ANN) to predict the claim frequency for a travel insurance firm. I also evaluate which of the three models is most suitable for our dataset.

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iamkirankumaryadav/Loan

Loan Approval Prediction

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iamkirankumaryadav/Iris

Iris Data : Classification / Pattern Recognition, Predict the Class of Flower based on Available Attributes.

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NeonOstrich/Credit-Risk-Classification-using-Logistic-Regression

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.

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tmard/Credit-Risk-Classification

Supervised machine learning to train and evaluate models based on loan risk.

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sainikhilp/Pos_Neg_Movie_Classification

Given a set of text movie reviews that have been labeled positive or negative, a machine learning classification model should be trained and tested for predicting the nature of future movie reviews.

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sainikhilp/Telco_Customer_Churn_Prediction

This project aims at predicting whether a customer will continue with the Telco Service group or not. The data was analyzed and trained using decision trees and random forests algorithm

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Sridhar922/Water-Quality-Analysis

Water Quality Analysis

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kwr4/Customer-Satisfaction-Prediction

Machine Learning Model in Jupyter notebook using Python on a Customer Satisfaction Data Set to explore, visualize, test, train and predict. Xgb boost

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mohammadtavakoli78/Data-Mining

This is projects of Data Mining

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jaiminjariwala/Decision_Tree_Algorithm_Project

Penguin Species Prediction Using Decision Tree

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twigikit/algo-trading-homework

Implement an algo trading strategy that uses machine learning to automate the trade decisions

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jaiminjariwala/Logistic_Regression_Project

A Classification Model that can predict whether or not a person has presence of Heart Disease or not!

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lingumd/Credit_Risk_Analysis

Machine learning models for predicting credit risk in LendingClub dataset.

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twigikit/regression-modelling

Logistic regression model with train_test_split data

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schatzederwelt/customer-churn-prediction

Предиктивный анализ оттока клиентов

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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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Manaliagarwal/Student-Alcohol-Consumption-Detection-

With the Student Alcohol Consumption data set, we predict high or low alcohol consumption of students.

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Julian-Theis/stat-kiste

A collection of statistical methods

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roshansridhar/Multimodal-Sentiment-Analysis

Engaged in research to help improve to boost text sentiment analysis using facial features from video using machine learning.

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imane-ayouni/US-Airline-Twitter-Sentiment-Analysis

NLP and Classification techniques to analyze the sentiment in tweets

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Pradnya1208/Diabetes-classification-using-KNN

In this project, our goal is to Predict the onset of diabetes based on diagnostic measures using a Machine Learning algorithm. We are focusing on KNN Classifier for this problem.

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shaunwang1350/CreditLoans_MachineLearning

Credit risk is an inherently unbalanced classification problem, as the number of good loans easily outnumber the number of risky loans. I employed Machine Learning techniques to train and evaluate models with unbalanced classes. I used imbalanced-learn and scikit-learn libraries to build and evaluate models using resampling. I also evaluated the performance of these models and made a recommendation on whether they should be used to predict credit risk.

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