f-measure

There are 0 repository under f-measure topic.

lartpang / PySODEvalToolkit
PySODEvalToolkit: A Python-based Evaluation Toolbox for Salient Object Detection and Camouflaged Object Detection
python3 metrics metrics-visualization pr-curve fm-curve s-measure f-measure e-measure mae saliency saliency-detection salient-object-detection latex evaluation evaluation-metrics evaluation-framework evaluator camouflaged-object-detection co-saliency co-salient-object-detection
Language:Python 146
zzhanghub / eval-co-sod
PyTorch-Based Evaluation Tool for Co-Saliency Detection
co-saliency salient-object-detection pytorch evaluation f-measure e-measure s-measure auc pr-curve roc-curve average-precision mae mean-absolute-error python
Language:Python 92
Mehrdad-Noori / Saliency-Evaluation-Toolbox
An Evaluation Toolbox for Salient Object Detection
saliency-detection salient-object-detection e-measure s-measure f-measure toolbox segmentation
Language:Python 33
hamidsadeghi68 / face-clustering
Clustering Algorithms and their Application to Facial Image Analysis
face-clustering face-recognition face-detection awesome face facecup agglomerative arcface db-scan dlib facenet kmeans mtcnn f-measure purity rand-index nmi normalized-mutual-info clustering insightface
Language:Jupyter Notebook 18
eXascaleInfolab / xmeasures
Extremely fast evaluation of the extrinsic clustering measures: various (mean) F1 measures and Omega Index (Fuzzy Adjusted Rand Index) for the multi-resolution clustering with overlaps/covers, standard NMI, clusters labeling
clustering-evaluation benchmark-measures quality-measures f1-score nmi omega-index covers-evaluation extrinsic-quality-measures f-measure fuzzy-adjusted-rand-index overlapping-community-evaluation ari accuracy-metrics
Language:C++ 17
Mr-TalhaIlyas / Evaluation-Metrics-Package-Tensorflow-PyTorch-Keras
ML/CNN Evaluation Metrics Package
precision-recall dice-coefficient confusion-matrix classification-accuracy curve precision-recall-curve roc-curve f-measure average-precision segmentaion-metrics classification-metrics object-detection-metrics
9
alaahossam / Networks-Anomaly-Detection
Networks Anomaly Detection using Supervised learning Algorithms such as Kmeans implementation , Spectral clustering implementation, DBMS implementation and Agglomerative Hierarchical Clustering. We also used external and internal measures to evaluate the clustering such as F1-score, purity, precision, recall and pairwise measures.
dbscan-clustering f-measure kmeans-clustering machine-learning-algorithms pairwise-calculations purity spectral-clustering
Language:Jupyter Notebook 1
LuceneCISI
Berozain / LuceneCISI
Information Retrieval with Lucene and CISI dataset. Index documents and search between them with IB, DFR, BM-25, TF-IDF, Boolean, Axiomatic, LM-Dirichlet similarity and calculate Recall, Precision, MAP (Mean Average Precision) and F-Measure
cisi information-retrieval lucene axiomatics bm-25 dfr f-measure mean-average-precision precision recall recall-precision tf-idf lm-dirichlet ib
Language:Java 1
semnan-university-ai / confusion-matrix-classification
Calculate Precision & Recall & F-Measure & Accuracy with Confusion Matrix (TP, TN, FP, FN)
confusion-matrix f-measure precision recall
1
bunji2 / metrics
Sample of metrics by GoLang
golang metrics f-measure accuracy-metrics prescion-metrics recall-metrics
Language:Go
melaanya / f_macro_optimization
Threshold optimization for F measure of macro-averaged precision and recall
f-measure machine-learning optimization
Language:Python