model-evaluation-metrics
There are 31 repositories under model-evaluation-metrics topic.
encord-team/text-to-image-eval
Evaluate custom and HuggingFace text-to-image/zero-shot-image-classification models like CLIP, SigLIP, DFN5B, and EVA-CLIP. Metrics include Zero-shot accuracy, Linear Probe, Image retrieval, and KNN accuracy.
SayamAlt/Language-Detection-using-fine-tuned-XLM-Roberta-Base-Transformer-Model
Successfully developed a language detection transformer model that can accurately recognize the language in which any given text is written.
Aayush711/Federated-Learning-Project
This repository contains a project showcasing Federated Learning using the EMNIST dataset. Federated Learning is a privacy-preserving machine learning approach that allows a model to be trained across multiple decentralized devices or servers holding local data samples, without exchanging them.
yash-dahima/CSE523-Machine-Learning-2023-Air-Quality-Prediction
This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.
Pratham-mehta/Real-time-Driver-Drowsiness-Detection-System-Using-Deep-Learning
CS-GY 6953 Deep Learning Major Project
Schuch666/eva3dm
A package to evaluate 3d weather and air quality models
ishita48/Breast-Cancer-Diagnosis-ML-model
This breast cancer diagnosis project evaluates various machine learning models to effectively classify breast masses as benign or malignant. SVM and Logistic Regression excel in identifying positive cases, leveraging their robust performance metrics, while Neural Networks show promising results and offer opportunities for further enhancement!
Abhi3886/LoanApprovalAnalysis
Loan Approval Analysis involves building a machine learning model to predict whether a loan will be approved or not based on various customer features
Amanrai2004/Diamondpricepredication
About Machine Learning and Data Analysis on Diamonds Dataset
AnxiousCodeGeek/heartAttack-modelEvaluation
Performed model evaluation using evaluation metrics such as accuracy, precision, recall, F1-score etc. Then model interpretation using feature importance, SHAP and LIME. Finally , evaluated model robustness and stability through techniques like bootstrapping or Monte Carlo simulations.
dell-datascience/Applied-Machine-Learning-in-Python
Coursera Applied Machine Learning in Python
ehtisham-sadiq/Linear-Regression-Step-by-Step
"Linear Regression Step by Step" is a repository that provides a comprehensive notebook with step-by-step examples, exercises and libraries to understand and implement Linear Regression easily.
ImM0rTaLBB/UCI-Heart-Disease-Data-Mining
UCI Heart Disease - Feature Engineering and Models Evaluation
pjbk/Wine-Quality-Prediction
Quality Prediction of red and white wine
PoojanDoshi11/Speech_Detection
🗣️ Speech Type Detection is a Flask app to classifies text into categories like "Hate Speech," "Offensive Language," or "No Hate or Offensive Language" with 87.3% accuracy. It offers a user-friendly interface for text input and prediction, using machine learning algorithms. Idea for managing online inappropriate language. 🌐🔍.
SayamAlt/Liver-Cirrhosis-Stage-Prediction
Successfully established a machine learning model which can determine whether an individual is vulnerable to the Cirrhosis disease or not by predicting its corresponding stage based on a unique set of medical features such as Cholesterol, Prothrombin, etc. pertaining to that person.
sflyranger/Spam-Detection-Pipelines-
A spam detection model built to handle imbalanced data using small pipelines. This project walks through text preprocessing, model tuning, and performance evaluation with ROC-AUC curves and classification reports, focusing on practical steps like using XGBoost and TFIDF for spam classification.
alexandrumonahov/mewto
mewto is an R package that allows you to experiment with different thresholds for classification of prediction results in the case of binary classification problems and visualize various model evaluation metrics, confusion matrices and the ROC curve. It also allows you to calculate the optimal threshold based on a weighted evaluation criterion.
Anas436/E-Commerce-Customer-Churn-Prediction
E-Commerce Customer Churn Prediction using Machine Learning
arqchicago/rfc-heart
random forest classification (with hyperparameter tuning) on heart disease dataset.
beenish-Ishtiaq/DEP-Task-1-House-Price-Prediction
This project focuses on building a model to predict house prices in California using various features such as location, size, and number of bedrooms. The project includes data cleaning, feature engineering, and model training with Linear Regression and Random Forest algorithms.
bushra-ansari/Predicting-Term-Deposit-Subscription-by-a-Client-by-SVM-Classifier
Support Vector Machine Classification model is applied on bank dataset containing 41188 rows and 21 columns. The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to assess if the product (bank term deposit) would be ('yes') or not ('no') subscribed.
huseyincavusbi/breast_cancer_supervised
Supervised Learning Experiments on Wisconsin Breast Cancer Dataset
joanitolopo/eval-sampling-methods
🔍 Evaluating Sampling Techniques for Healthcare Insurance Fraud Detection in Imbalanced Dataset.
MaoucheMounir/Projet-RITAL-BagOfWords
Expérimentations sur divers modèles et méthodes de Machine Learning pour la classification de textes, et étude des mesures d'évaluation des modèles après normalisation des données
Amario1306619051/Fraud-Detection
"Retail transaction fraud detection project with machine learning models on the Data Mining Cup 2019 dataset."
fxckillua/Iris-accuracy-and-loss
Projeto que utiliza a base de dados Iris para calcular a acurácia e a função de perda de um modelo de aprendizado de máquina. Focado em análise de desempenho e avaliação de modelos.
GiovanniCornejo/spam-message-classifier
An ML-based project designed to accurately classify email messages as either spam or ham (non-spam)
pjbk/Iris-Species-Prediction
Predict the Class of Iris Species
rrambhia22/Regression-Predictive-Modeling-and-Analysis-of-Bitcoin-Hashrate
The primary objective of this study is to develop a dependable and precise prediction model to forecast alterations in Bitcoin's hash rate.
ShovalBenjer/Titanic---Machine-Learning-from-Disaster
This project explores machine learning techniques, focusing on data preprocessing, model building, and evaluation. It includes data analysis, visualization, various algorithms, and performance comparison. Key topics: data cleaning, feature engineering, model selection, hyperparameter tuning, and evaluation metrics.