Topic: model-evaluation-metrics Goto Github
Some thing interesting about model-evaluation-metrics
Some thing interesting about model-evaluation-metrics
model-evaluation-metrics,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.
User: aayush711
model-evaluation-metrics,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.
User: alexandrumonahov
model-evaluation-metrics,About Machine Learning and Data Analysis on Diamonds Dataset
User: amanrai2004
model-evaluation-metrics,"Retail transaction fraud detection project with machine learning models on the Data Mining Cup 2019 dataset."
User: amario1306619051
model-evaluation-metrics,E-Commerce Customer Churn Prediction using Machine Learning
User: anas436
model-evaluation-metrics,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.
User: anxiouscodegeek
model-evaluation-metrics,random forest classification (with hyperparameter tuning) on heart disease dataset.
User: arqchicago
model-evaluation-metrics,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.
User: beenish-ishtiaq
model-evaluation-metrics,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.
User: bushra-ansari
model-evaluation-metrics,Coursera Applied Machine Learning in Python
User: dell-datascience
model-evaluation-metrics,"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.
User: ehtisham-sadiq
model-evaluation-metrics,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.
Organization: encord-team
Home Page: https://encord.com
model-evaluation-metrics,An ML-based project designed to accurately classify email messages as either spam or ham (non-spam)
User: giovannicornejo
model-evaluation-metrics,Supervised Learning Experiments on Wisconsin Breast Cancer Dataset
User: huseyincavusbi
model-evaluation-metrics,UCI Heart Disease - Feature Engineering and Models Evaluation
User: imm0rtalbb
model-evaluation-metrics,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!
User: ishita48
model-evaluation-metrics,🔍 Evaluating Sampling Techniques for Healthcare Insurance Fraud Detection in Imbalanced Dataset.
User: joanitolopo
model-evaluation-metrics,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
User: maouchemounir
model-evaluation-metrics,Predict the Class of Iris Species
User: pjbk
model-evaluation-metrics,Quality Prediction of red and white wine
User: pjbk
model-evaluation-metrics,CS-GY 6953 Deep Learning Major Project
User: pratham-mehta
model-evaluation-metrics,The primary objective of this study is to develop a dependable and precise prediction model to forecast alterations in Bitcoin's hash rate.
User: rrambhia22
model-evaluation-metrics, Successfully developed a language detection transformer model that can accurately recognize the language in which any given text is written.
User: sayamalt
model-evaluation-metrics,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.
User: sayamalt
model-evaluation-metrics,A package to evaluate 3d weather and air quality models
User: schuch666
Home Page: https://schuch666.github.io/eva3dm/
model-evaluation-metrics,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.
User: shovalbenjer
model-evaluation-metrics,This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.
User: yash-dahima
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