Topic: accuracy-metrics Goto Github
Some thing interesting about accuracy-metrics
Some thing interesting about accuracy-metrics
accuracy-metrics,Breast Cancer Detection using Machine Learning
User: abhinavy789
accuracy-metrics,A project which examines the prevalence of fake news in light of communication breakthroughs made possible by the rise of social networking sites.
User: agyeyamishra
accuracy-metrics,Dance Forms Identification: A Deep Learning Classification Problem.
User: akarsh1
accuracy-metrics,Applying K Means and KNN on a multiclass dataset to make clusters and find nearest neighbours.
User: areesha-tahir
accuracy-metrics,This repository contains code for classifying galaxies into three classes: Galaxy, Quasar, and Star, using machine learning techniques. The dataset used in this project is the Sloan Digital Sky Survey (SDSS) dataset.
User: avid7-tech
accuracy-metrics,Resampling Tools for Time Series Forecasting with Modeltime
Organization: business-science
Home Page: https://business-science.github.io/modeltime.resample/
accuracy-metrics,Rank 16/98 MachineHack
User: chandrashekhar1227-ml
accuracy-metrics,In this project, the numeric digits are classified by using deep learning algorithm.
User: chandru-engineer
accuracy-metrics,Deep Learning Face Detection and Verification
User: danielmuthama
accuracy-metrics,Using Natural Language Processing alongside Machine Learning on Python to help detect fake product reviews on famous e-commerce sites with more accuracy!
User: dmittz
accuracy-metrics,Generalized Conventional Mutual Information (GenConvMI) - NMI for overlapping (soft, fuzzy) clusters (communities), compatible with standard NMI, pure C++ version (single executable)
Organization: exascaleinfolab
accuracy-metrics,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
Organization: exascaleinfolab
accuracy-metrics,What is "accuracy"? The effect of changing the decision threshold on a model's accuracy.
Organization: fau-masters-collected-works-cgarbin
accuracy-metrics,Voting Ensemble & Stock Prediction - Project Submission for Data Mining & Machine Learning Module
User: francaisse
accuracy-metrics,A Shiny R web application to estimate differences in diagnostic efficiency based on differences between single-condition cases.
User: gasparl
Home Page: https://gasparl.shinyapps.io/esdi/
accuracy-metrics,Prediction of Heart Disease using machine learning models
User: gugan91
accuracy-metrics,To Detect Sepsis Disease using six Classifiers on clinical data
User: hcyendluri
accuracy-metrics,Landscape of ML/DL performance evaluation metrics
User: hollobit
accuracy-metrics,Sinhala text extraction, preprocessing, and classification considering subject and domain.
User: isurie
accuracy-metrics,TakenMind Global Internship Program is recognized under United Nations Sustainable Development and Growth (SDG) and is a highly recognized International Certification Program. - Reference Link to the United Nations SDG #26437 TakenMind Program. TakenMind (powered by United Nations SDG Program) is offering a Global Internship in Data Analytics and Management.
User: jimoh1993
accuracy-metrics,A set of python scripts for spatially explicit accuracy assessments of binary, gridded geospatial data, e.g., for human settlement data mapping built-up (1) and not built-up (0) areas.
User: johannesuhl
accuracy-metrics,This repository, focus on password strength prediction. I have created an SVM model to classify whether password strength or medium or weak. After training the model, It has deployed on the Heroku platform.
User: krisharul26
accuracy-metrics,Implementation of SVM Classifier To Perform Classification on the dataset of Breast Cancer Wisconin; to predict if the tumor is cancer or not.
User: lailamahmoudi
accuracy-metrics,A reinforcement learning model specialized in stock prediction utilizing deep learning techniques, incorporating reward mechanisms, compatible with any machine equipped with Python.
User: lex-hue
accuracy-metrics,Build a model which will predict whether an individual will hire an attorney or not.
User: manasik29
accuracy-metrics,learning python day 6
User: maryamsoftdev
accuracy-metrics,A simple Python model that uses TFIDF Vectorizer and Passive Agressive Classifier to detect fake and irrelevant news
User: memeghaj10
accuracy-metrics,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
accuracy-metrics,This Project is based on Neural Network to classify between Dogs and Cats.
User: niklesh99
accuracy-metrics,Images consist of visual components such as color, shape, and texture. These components stand as the primary basis with which images are distinguished. A content-based image retrieval system extracts these primary features of an image and checks the similarity of the extracted features with those of the image given by the user. A group of images similar to the query image fed is obtained as a result. This paper proposes a new methodology for image retrieval using the local descriptors of an image in combination with one another. HSV histogram, Color moments, Color auto correlogram, Histogram of Oriented Gradients, and Wavelet transform are used to form the feature descriptor. In this work, it is found that a combination of all these features produces promising results that supersede previous research. Supervised learning algorithm, SVM is used for classification of the images. Wang dataset is used to evaluate the proposed system.
User: niranjana1997
accuracy-metrics,The project is an integral cog in Computer Vision and Artificial Intelligence and Machine learning. It aims to determine the activity of a human from a video provided to the machine. It is a step forward in solving various problems like surveillance, fall detection for elderly or sick people, robotics and computer interaction, security among many others. We want a higher accuracy in doing so with respect to the videos used for training the machine.
User: proacc2022
accuracy-metrics,Three skin diseases images classified with support vector machine. The dataset is collected from kaggle and some other sources. This code is used in a research work in one of the IEEE conferences.
User: ptsourav21
Home Page: https://ieeexplore.ieee.org/document/10099354
accuracy-metrics,Evaluation of the performance of classification models can be facilitated through a combination of calculating certain types of performance metrics and generating model performance evaluation graphics. The purpose of this exercise is to calculate a suite of classification model performance metrics via Python code functions.
User: randleon
accuracy-metrics,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
accuracy-metrics,Scrapped tweets using twitter API (for keyword ‘Netflix’) on an AWS EC2 instance, ingested data into S3 via kinesis firehose. Used Spark ML on databricks to build a pipeline for sentiment classification model and Athena & QuickSight to build a dashboard
User: rochitasundar
accuracy-metrics,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
accuracy-metrics,This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.
User: scrayil
accuracy-metrics,End-to-end implementation of Spam Detection in Email using Machine Learning, Python, Flask, Gunicorn, Scikit-Learn, and Logistic Regression on the Heroku cloud application platform.
User: shehansanjula
Home Page: https://spam-email-filtering-system.shehansanjula.dev
accuracy-metrics,Multiple Object Tracking in video Using Deep learning
User: shreyaskorde16
accuracy-metrics,[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes
Organization: squaredev-io
Home Page: https://squaredev.io/whitebox/
accuracy-metrics,Big Data Project - SSML - Spark Streaming for Machine Learning
User: swarna0712
accuracy-metrics,Solved Classification Problems
User: syrineb11
accuracy-metrics,Supervised Machine Learning project with KNN, decision tree, random forest and adaboost algorithms
User: tezam84
accuracy-metrics,This Model is used to Predict Emails data. Either emails are Spam or Normal (Ham) Mail.
User: umarrajpoot
accuracy-metrics,Bei der Vermessung eines physischen Raumes ist das Ergebnis eine Punktwolke. Diese Punktwolke beschreibt dann ausgewählte Punkte im Raum, zum Beispiel auf den Wänden und der Decke. Wenn diese Punkte in zwei seperaten Messungen gemessen werden, vielleicht sogar von unterschiedlichen Geräten, soll hinterher herausgefunden werden wie genau diese Punktwolken übereinstimmen. Dafür gibt es zwei grundsätzlich verschiedene Methoden. Diese sollen hier verglichen werden.
User: walkerdustin
accuracy-metrics,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/
accuracy-metrics,To Detect Early Sepsis Disease
User: ymeghana
Home Page: https://sepsis-detection.herokuapp.com/
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