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

Neo: Hierarchical Confusion Matrix Visualization (CHI 2022)

Explore hands-on machine learning projects, resources, and collaborative opportunities in this GitHub repository.

Tool to analyze a confusion matrix from performance of a classification model.

Data Science Project - Full Depth analysis AND Prediction Using Decision Tree and Random Forest

📔 This repository delves into Logistic Regression for loan approval prediction at LoanTap. It covers data preprocessing, model development, evaluation metrics, and strategic business recommendations. Explore model optimization techniques such as confusion matrix, precision, recall, Roc curve and F1 score to effectively mitigate default risks.

Dynamic Confusion Matrix and Performance Metrics Visualization Tool

This is a group project in the Data Science for Business I course where we took a data-driven approach to foster employee retention and enhance operational efficiency by building predictive models on Python.

An in-depth exploration of logistic regression models, including data cleaning, model building, and performance evaluation on various datasets.

A Performance Study of Naive Bayes Classifier in Advertisement Analysis

Repositorio creado para almacenar archivos, script y el informe final del curso de modelamiento estadístico del Diplomado en Big Data de la Pontificia Universidad Católica de Chile.

A model that makes use of SVM, Logistic Regression, Naive Bayes, Dense NN to judge whether a review is positive or negative

Classification of Sober and Intoxicated Faces using Image Analysis

This project aims to tackle this problem by developing a system that can effectively detect fake news using machine learning techniques.

Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

These are all of my machine learning codes.You can find every code about machine learning.

Machine learning utilities for .NET. Confusion matrix, intersection over union, etc.

This repo is for finding whether a PDF file in json format contains virus or not by classifying it into Malicious or Benign using Classification algorithms.

Content: Machine Learning, Logistic regression steps, Probability matrix, Confusion matrix, Accuracy score, Recall value, Data preprocessing, Label encoding, Scaling the data, Splitting train test data, Running Logistic Regression, Y prediction on test data, Class imbalance, Type 1 & Type 2 errors.