Topic: precision-recall Goto Github
Some thing interesting about precision-recall
Some thing interesting about precision-recall
precision-recall,CNN model to classify garbage
User: aalaa4444
precision-recall,Identifying Books on Library Shelves using Supervised Deep Learning.
User: adarsh-sophos
precision-recall,Resample precision-recall curves correctly!
User: ameya98
precision-recall,Trained MATLAB models for 82% precision/80% recall, optimized with blob analysis for 25% performance boost. User-friendly alarm system with 500+ engaged users.
User: ash-0521
precision-recall,Using Collaborative Filtering predicting Movie Rating and K-nearest Neighbours & SVM algorithms for Number ClassificationNumber Classification
User: ashwin0229
precision-recall,LSTM based model for Named Entity Recognition Task using pytorch and GloVe embeddings
User: baaraban
precision-recall,Supervised Machine Learning and Credit Risk
User: cbrito3
precision-recall,Submissions for Data Science: Principles, Algorithms, and Applications (CS839) @ UW-Madison
User: chakshuahuja
precision-recall,In this project, the numeric digits are classified by using deep learning algorithm.
User: chandru-engineer
precision-recall,Unofficial Python implementation of "Precision and Recall for Time Series".
Organization: compml
Home Page: https://papers.nips.cc/paper/2018/file/8f468c873a32bb0619eaeb2050ba45d1-Paper.pdf
precision-recall,Mail SPAM Detector
User: danort92
precision-recall,Insurance Cross Sell Opportunity Forecast through machine learning algorithm
User: danort92
precision-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.
User: deadskull7
precision-recall,Evaluation of 3D detection and diagnosis performance βgeared towards prostate cancer detection in MRI.
Organization: diagnijmegen
Home Page: https://pi-cai.grand-challenge.org/
precision-recall,Using supervised machine learning to predict credit risk. Trying oversampling, under sampling, combination sampling and ensemble learning to find the model with the best fit
User: emaynard10
precision-recall,Apply supervised machine learning techniques and an analytical mind on data collected for the U.S. census to help CharityML (a fictitious charity organization) identify people most likely to donate to their cause
User: gouravaich
precision-recall,Compared the metrics and performance of different classification algorithms on Heart Failure dataset from UCI ML Repository
User: grvnair
precision-recall,Information Retrieval models implemented in Python
User: igoraugust0
precision-recall,Lead scoring case study
User: jitalen
precision-recall,Built a simple search system using Lucene. Indexed 100 text documents using the bbc-news sports dataset. Showed the impact of indexing the data well on precision and recall. Have included the queries used to arrive at the precision and recall.
User: kamatameya9
precision-recall,A Swift implementation of mAP computation for Yolo-style detections
User: laclouis5
precision-recall,Using 21 predictor variables and applying simple Logistic Regression, predicting whether a particular customer will switch to another telecom provider or not. In telecom terminology, this is referred to as churning and not churning, respectively.
User: lakshaykakkarr
precision-recall,(projeto ainda nΓ£o finalizado) - Este repositΓ³rio contΓ©m um projeto de uma seguradora deseja comeΓ§ar a vender seguro de veΓculos para clientes que jΓ‘ possuem plano de saΓΊde.
User: lucas-penalva
precision-recall,Report various statistics stemming from a confusion matrix in a tidy fashion. π―
User: m-clark
Home Page: https://m-clark.github.io/confusionMatrix/
precision-recall,The objective of this analysis isΒ to find patterns within the dataset to gain further understanding of the data and leverage it to choose a machine learning algorithm that can recommend a suitable profile for the applicants whose visa should be certified or denied
User: mandyiv
precision-recall,πCourse 3: Machine Learning Specialization course of Coursera by the University of Washington on Classification
User: mayankchaudhary26
precision-recall,ML/CNN Evaluation Metrics Package
User: mr-talhailyas
precision-recall,Developed a Convolutional Neural Network based on VGG16 architecture to diagnose COVID-19 and classify chest X-rays of patients suffering from COVID-19, Ground Glass Opacity and Viral Pneumonia. This repository contains the link to the dataset, python code for visualizing the obtained data and developing the model using Keras API.
User: neeraj1397
precision-recall,Fraud detection with SMOTE (Synthetic Minority Over-sampling Technique)
User: neoyung
precision-recall,Human Resources Analytics
User: ola76
Home Page: https://www.kaggle.com/datasets/sanjanchaudhari/employees-performance-for-hr-analytics
precision-recall,BGU, Information Retrieval final project. Search-engine, Wikipedia corpus.
User: omerhanan1
precision-recall,An information retrieval system which consists of various techniques' implementations like indexing, tokenization, stopping, stemming, page ranking, snippet generation and evaluation of results
User: parshva45
precision-recall,Machine Learning: Code and Projects
User: philipmccormick
precision-recall,Amex Analyze This is a data science competition held by American Express across all the Indian Institute of Technology Institutes across India. I had participated in this competition in 2018, it was based on predictive modelling where we need to train a model to solve a bank problem - Analyze This 2018
User: prakharpartha
precision-recall,Most popular metrics used to evaluate object detection algorithms.
User: rafaelpadilla
precision-recall,Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
User: rafaelpadilla
precision-recall,ML-FinFraud-Detector is a machine learning project for detecting financial transaction fraud. Utilizing XGBoost, precision-recall, and ROC curves, it provides accurate fraud detection. Explore feature importance, evaluate model performance, and enhance financial security with this comprehensive fraud detection solution.
User: robertrusev
precision-recall,The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate profitable policies for cancelations & refunds.
User: rochitasundar
precision-recall,The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidates more likely to have the visa certified.
User: rochitasundar
precision-recall,The goal of this project is to develop a machine learning model that can help banks to identify customers who are likely to churn and take appropriate measures to retain them
User: saadtariq01dataanalyst
precision-recall,
User: sajidahmed12
precision-recall,Time-series Aware Precision and Recall for Evaluating Anomaly Detection Methods
User: saurf4ng
precision-recall,Machine learning utility functions and classes.
User: stefmolin
precision-recall,Resampling exercise to predict accuracy, precision, and sensitivity in credit-loan risk
User: tracari
precision-recall,Classification problem using multiple ML Algorithms
User: viveksagarsingh
precision-recall,Classification Metric Manager is metrics calculator for machine learning classification quality such as Precision, Recall, F-score, etc.
Organization: winkam
Home Page: https://winkam.com/
precision-recall,Evaluate a detection model performance
User: xu-justin
precision-recall,
User: zakarich
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