Welcome to Permetrics’s documentation!
PerMetrics is a python library for performance metrics of machine learning models. We aim to implement all performance metrics for problems such as regression, classification, clustering, … problems. Helping users in all field access metrics as fast as possible
Free software: GNU General Public License (GPL) V3 license
Total metrics: 111 (47 regression metrics, 20 classification metrics, 44 clustering metrics)
Documentation: https://permetrics.readthedocs.io/en/latest/
Python versions: >= 3.7.x
Dependencies: numpy, scipy
- Regression Metrics
- EVS - Explained Variance Score
- ME - Max Error
- MAE - Mean Absolute Error
- MSE - Mean Squared Error
- BE - Mean Bias Error
- RMSE - Root Mean Square Error
- MSLE - Mean Squared Logarithmic Error
- MedAE - Median Absolute Error
- MRE - Mean Relative Error
- MPE - Mean Percentage Error
- MAPE - Mean Absolute Percentage Error
- SMAPE - Symmetric Mean Absolute Percentage Error
- MAAPE - Mean Arctangent Absolute Percentage Error
- MASE - Mean Absolute Scaled Error
- NSE - Nash-Sutcliffe Efficiency
- NNSE - Normalized NSE
- WI - Willmott Index
- R - Pearson’s Correlation Index
- AR - Absolute Pearson’s Correlation Index
- R2 - Coefficient of Determination
- AR2 - Adjusted R2
- CI - Confidence Index
- R2s - (Pearson’s Correlation Index)**2
- DRV - Deviation of Runoff Volume
- KGE - Kling-Gupta Efficiency
- GINI - GINI Coefficient
- PCD - Prediction of Change in Direction
- CE - Cross Entropy
- KLD - Kullback-Leibler Divergence
- JSD - Jensen-Shannon Divergence
- VAF - Variance Accounted For
- RAE - Relative Absolute Error
- A10 - A10 index
- A20 - A20 index
- A30 - A30 index
- NRMSE - Normalized Root Mean Square Error
- RSE - Residual Standard Error
- COV - Covariance
- COR - Correlation
- EC - Efficiency Coefficient
- OI - Overall Index
- CRM - Coefficient of Residual Mass
- RE - Relative Error
- AE - Absolute Error
- SE - Squared Error
- SLE - Squared Log Error
- EVS - Explained Variance Score
- Classification Metrics
- Accuracy Score (AS)
- Cohen Kappa Score (CKS)
- F1 Score (F1S)
- F2 Score (F2S)
- F-Beta Score (FBS)
- GINI Index
- G-Mean Score (GMS)
- Precision Score (PS)
- Negative Predictive Value (NPV)
- Recall Score (RS)
- Specificity Score (SS)
- Matthews Correlation Coefficient (MCC)
- Hamming Score (HS)
- Lift Score (LS)
- Jaccard Similarity Index (JSI)
- ROC-AUC
- Accuracy Score (AS)
- Clustering Metrics
- 1
Thieu Nguyen, Giang Nguyen, and Binh Minh Nguyen. Eo-cnn: an enhanced cnn model trained by equilibrium optimization for traffic transportation prediction. Procedia Computer Science, 176:800–809, 2020.
- 2
Thieu Nguyen, Nhuan Tran, Binh Minh Nguyen, and Giang Nguyen. A resource usage prediction system using functional-link and genetic algorithm neural network for multivariate cloud metrics. In 2018 IEEE 11th conference on service-oriented computing and applications (SOCA), 49–56. IEEE, 2018.
- 3
Takeyoshi Kato. Prediction of photovoltaic power generation output and network operation. In Integration of Distributed Energy Resources in Power Systems, pages 77–108. Elsevier, 2016.
- 4
Thieu Nguyen, Binh Minh Nguyen, and Giang Nguyen. Building resource auto-scaler with functional-link neural network and adaptive bacterial foraging optimization. In International Conference on Theory and Applications of Models of Computation, 501–517. Springer, 2019.
- 5
Timothy O Hodson, Thomas M Over, and Sydney S Foks. Mean squared error, deconstructed. Journal of Advances in Modeling Earth Systems, 13(12):e2021MS002681, 2021.
- 6
Binh Minh Nguyen, Trung Tran, Thieu Nguyen, and Giang Nguyen. An improved sea lion optimization for workload elasticity prediction with neural networks. International Journal of Computational Intelligence Systems, 15(1):90, 2022.
- 7
Thieu Nguyen, Bao Hoang, Giang Nguyen, and Binh Minh Nguyen. A new workload prediction model using extreme learning machine and enhanced tug of war optimization. Procedia Computer Science, 170:362–369, 2020.
- 8
Tu Nguyen Thieu Nguyen, Binh Minh Nguyen, and Giang Nguyen. Efficient time-series forecasting using neural network and opposition-based coral reefs optimization. International Journal of Computational Intelligence Systems, 12(2):1144–1161, 2019.
- 9
Chengyu Xie, Hoang Nguyen, Xuan-Nam Bui, Van-Thieu Nguyen, and Jian Zhou. Predicting roof displacement of roadways in underground coal mines using adaptive neuro-fuzzy inference system optimized by various physics-based optimization algorithms. Journal of Rock Mechanics and Geotechnical Engineering, 13(6):1452–1465, 2021.
- 10
Ali Najah Ahmed, To Van Lam, Nguyen Duy Hung, Nguyen Van Thieu, Ozgur Kisi, and Ahmed El-Shafie. A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem. Applied Soft Computing, 105:107282, 2021.
- 11
Rodrigo Dlugosz da Silva, Marcelo Augusto de Aguiar, Marcelo Giovanetti Canteri, Juliandra Rodrigues Rosisca, Nilson Aparecido Vieira Junio, and others. Reference evapotranspiration for londrina, paraná, brazil: performance of different estimation methods. Semina: Ciências Agrárias, 38(4):2363–2374, 2017.
- 12
Nguyen Van Thieu, Surajit Deb Barma, To Van Lam, Ozgur Kisi, and Amai Mahesha. Groundwater level modeling using augmented artificial ecosystem optimization. Journal of Hydrology, 617:129034, 2023.
- 13
Binh Minh Nguyen, Bao Hoang, Thieu Nguyen, and Giang Nguyen. Nqsv-net: a novel queuing search variant for global space search and workload modeling. Journal of Ambient Intelligence and Humanized Computing, 12:27–46, 2021.
- 14
Kapil Gupta. An integrated batting performance analytics model for women’s cricket using principal component analysis and gini scores. Decision Analytics Journal, 4:100109, 2022.
- 15
John R Hershey and Peder A Olsen. Approximating the kullback leibler divergence between gaussian mixture models. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing-ICASSP'07, volume 4, IV–317. IEEE, 2007.
- 16
Bent Fuglede and Flemming Topsoe. Jensen-shannon divergence and hilbert space embedding. In International symposium onInformation theory, 2004. ISIT 2004. Proceedings., 31. IEEE, 2004.
- 17
Karl D Stephen and Alireza Kazemi. Improved normalization of time-lapse seismic data using normalized root mean square repeatability data to improve automatic production and seismic history matching in the nelson field. Geophysical Prospecting, 62(5):1009–1027, 2014.
- 18
Karl G Jöreskog. Structural analysis of covariance and correlation matrices. Psychometrika, 43(4):443–477, 1978.
- 19
Rolla Almodfer, Mohamed E Zayed, Mohamed Abd Elaziz, Moustafa M Aboelmaaref, Mohammed Mudhsh, and Ammar H Elsheikh. Modeling of a solar-powered thermoelectric air-conditioning system using a random vector functional link network integrated with jellyfish search algorithm. Case Studies in Thermal Engineering, 31:101797, 2022.
- 20
Bernard Desgraupes. Clustering indices. University of Paris Ouest-Lab Modal’X, 1(1):34, 2013.