K-folds with returns for F1, Accuracy, Precision, Recall and counts for each prediction

Classification performance standards such as accuracy, precision, recall, confusion matrix, F1, ROC, AUC. Take MNIST as example.

A classifier that takes X-RAY or CT-SCAN to classify positive or negative COVID19 with 99% accuracy, 97% recall (macro avg) and 91% precision (macro avg).

fraud detection outputting a confusion matrix, precision, recall, f1 score, roc auc and accuracy

Precision, recall, f1-score, AUC, loss, accuracy and ROC curve are often used in binary image recognition evaluation issue. The repository calculates the metrics based on the data of one epoch rath…

Implementations of various performance metrics such as F1 score, Precision, Recall, Accuracy, Confusion Matrix, ROC-AUC score, etc., from scratch, without utilizing the sklearn libraries.

Classification Algorithms and Model Evaluation Logistic Regression Confusion Matrix Precision, Recall, Accuracy, F1 Score ROC AUC Curve Deciding Binary Classifier threshold

this is the heart disease prediction code by using machine learning algorithms also gives accuracy, precision ,recall,F1 score,AUC-ROC

Application software in Python 3 to evaluate the factor of safety against sliding of slopes made of Blocks-In-Matrix materials.

CNN+BiLSTM+Attention Multivariate Time Series Prediction implemented by Keras

source code of AAAI 2024 paper "Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization".

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

A family of open-sourced Mixture-of-Experts (MoE) Large Language Models

异常检测算法

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Purposed a network traffic classification and prediction model based on CNN, TCN and Attention mechanism.

Improving prediction of punching shear strength of reinforced concrete flat slabs without transverse reinforcements using machine learning and deep learning with grid search

Prediction of Shear Strength of RC Deep Beam

A code that uses machine learning to predict shear strength of columns. Including model training and comparison, comparison with current specifications and comparison of parameter importance.

Implementing ensemble learning methods for shear strength prediction of RC deep beams with/without web reinforcements

Accurate prediction of the shear strength of the interface between old and new concrete (cold joints) is essential for the design or assessment of precast and retrofitted concrete structures. The X…

The geographic prediction of landslide occurrence is undertaken by assessing whether a slope may be stable or unstable. In other words, current practices treat slopes where a single landslide occur…

Landslide prediction with random forest algorithm using five parameters (elevation, slope, curvature, NDVI, and landuse)

a tool to collect codes into a html document with syntax highlighted, written in python