confusion-matrix
There are 783 repositories under confusion-matrix topic.
sepandhaghighi/pycm
Multi-class confusion matrix library in Python
wcipriano/pretty-print-confusion-matrix
Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib
apple/ml-hierarchical-confusion-matrix
Neo: Hierarchical Confusion Matrix Visualization (CHI 2022)
squaredev-io/whitebox
[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes
cheind/tf-matplotlib
Seamlessly integrate matplotlib figures as tensorflow summaries.
deadskull7/Pneumonia-Diagnosis-using-XRays-96-percent-Recall
BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.
metriculous-ml/metriculous
Measure and visualize machine learning model performance without the usual boilerplate.
kaanakan/object_detection_confusion_matrix
Python class for calculating confusion matrix for object detection task
sharmaroshan/Fraud-Detection-in-Online-Transactions
Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Frauds is less than 0.00005 thus, simply applying Classification Algorithm may result in Overfitting
deadskull7/One-Stop-for-COVID-19-Infection-and-Lung-Segmentation-plus-Classification
✋🏼🛑 This one stop project is a complete COVID-19 detection package comprising of 3 tasks: • Task 1 --> COVID-19 Classification • Task 2 --> COVID-19 Infection Segmentation • Task 3 --> Lung Segmentation
aditya9211/SVHN-CNN
Google Street View House Number(SVHN) Dataset, and classifying them through CNN
snatch59/cnn-svm-classifier
Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
PENGZhaoqing/kdd99-scikit
Solutions to kdd99 dataset with Decision tree and Neural network by scikit-learn
alyakhtar/AQI-Delhi
Predicting air pollution level in a specific city
arvkevi/disarray
Confusion matrix metrics directly from your pandas DataFrame
wangjksjtu/rl-perturbed-reward
Reinforcement Learning with Perturbed Reward, AAAI 2020
the-mrinal/ML-Notebook
Karma of Humans is AI
suhagba/Final-year-project-deep-learning-models
Deep learning for freehand sketch object recognition
Altimis/Confusion-matrix-for-Mask-R-CNN
Confusion matrix for Mask R-CNN (Matterport implementation)
JingweiToo/Machine-Learning-Toolbox
This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, and etc., which are simpler and easy to implement.
oneoffcoder/py-pair
Pairwise association measures of statistical variable types
indrapaul824/Coronary-Heart-Disease-Prediction
This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project
hollobit/ML_evaluation_metrics
Landscape of ML/DL performance evaluation metrics
kuixu/pytorch_online_plotter
Online meter ploter for pytorch. Real time ploting Accuracy, Loss, mAP, AUC, Confusion Matrix
aquatiko/sentiment-analysis-TfIdf-vectorizer-method
Sentiment Analysis of movie reviews by sklearn's naive bayes and TfIdf word vectorizer.
Chinmayrane16/MNIST-Digit-Recognizer-CNN-Keras-99.66
Used the Dataset "MNIST Digit Recognizer" on Kaggle. Trained Convolutional Neural Networks on 42000 Training Images and predicted labels on 28000 Test Images with an Validation Accuracy of 99.52% and 99.66% on Kaggle Leaderboard.
simongeek/KerasVGGcifar10
Keras VGG implementation for CIFAR-10 classification Tutorial
sahilsharma884/Music-Genre-Classification
Perform three types of feature extraction: STFT, MFCC and MelSpectrogram. Apply CNN/VGG with or without RNN architecture. Able to achieve 95% accuracy.
sumanth-bmsce/Deep-Neural-Network-for-Clustering
Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means technique
mahesh147/Logistic-Regression
A very basic implementation of Logistic Regression classifier in python.
stefmolin/ml-utils
Machine learning utility functions and classes.
fcakyon/confplot
Confusion Matrix in Python: Plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib
fischlerben/Machine-Learning-Credit-Risk
Machine-Learning project that uses a variety of credit-related risk factors to predict a potential client's credit risk. Machine Learning models include Logistic Regression, Balanced Random Forest and EasyEnsemble, and a variety of re-sampling techniques are used (Oversampling/SMOTE, Undersampling/Cluster Centroids, and SMOTEENN) to re-sample the data. Evaluation metrics like the accuracy score, classification report and confusion matrix are generated to compare models and determine which suits this particular set of data best.
koushikkumarl/capsuleNetwork_cancerclassification
Image classification on lung and colon cancer histopathological images through Capsule Networks or CapsNets.
m-clark/confusionMatrix
Report various statistics stemming from a confusion matrix in a tidy fashion. 🎯
mansipatel2508/Network-Intrusion-Detection-with-Feature-Extraction-ML
The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.