Topic: classification-report Goto Github
Some thing interesting about classification-report
Some thing interesting about classification-report
classification-report,classify the Size_Categorie using SVM
User: abhik35
classification-report,Customer Retention Deep Learning Model
User: adil-imran
classification-report,Using a dataset provided by Airbnb, analysis and predictions will be made to understand what effects the total price of an Airbnb
User: ahing
classification-report,Different networks, 2D CNN, 1X1 filter, VGG16 and Inception network is used for predicting breast cancer from histopathological images. Performance of different models are compared and found out that InceptionNet performed the best.
User: aiswarya-nandakumar
classification-report,Objective: The department wants to build a model that will help them identify the potential customers who have a higher probability of purchasing the loan. This will increase the success ratio while at the same time reducing the cost of the campaign.
User: anooper1999
classification-report,Feature Engineering and Prediction of Survivors on the Titanic Dataset
User: arnav1312
classification-report,Building a model to classify student grade based on various factors and conducting exploratory data analysis
User: asood0113
classification-report,"TensorFlow Image Classification Project" This project demonstrates image classification using TensorFlow. The CIFAR-10 dataset, consisting of 60,000 32x32 color images across 10 classes, is explored and analyzed. Key components include data loading, dataset characteristics, and a machine learning model built using the functional API.
User: billy-enrizky
Home Page: https://billy-enrizky.github.io/TensorFlow-Image-Classification/
classification-report,The project aims to apply Naives Bayes on TF-IDF and Word2Vec Models .Use one of Selection Best Feature techniques to chose only features that contribute to the performance of the prediction
User: diem-ai
classification-report,We'll use Python to build and evaluate several machine learning models to predict credit risk. Being able to predict credit risk with machine learning algorithms can help banks and financial institutions predict anomalies, reduce risk cases, monitor portfolios, and provide recommendations on what to do in cases of fraud.
User: douguot
classification-report,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.
User: fischlerben
classification-report,Faces recognition example using eigenfaces and SVMs
User: gouravaich
classification-report,Sentiment analysis on customer reviews using machine learning and python
User: gperakis
classification-report,Iris Data : Classification / Pattern Recognition, Predict the Class of Flower based on Available Attributes.
User: iamkirankumaryadav
classification-report,NLP and Classification techniques to analyze the sentiment in tweets
User: imane-ayouni
classification-report,NU Bootcamp Module 20
User: jleigh101
classification-report,A collection of statistical methods
User: julian-theis
classification-report,This is in regard to algorithmic trading bot with the use of machine learning to predict potential returns and actual returns.
User: juzcho
classification-report,This group project aims to predict the arrest of different types of crime given a specific input (day/ location/etc.) using machine learning models.
User: karla-flores
classification-report,Supervised Machine Learning and Credit Risk
User: keyoumao
classification-report,Machine Learning Model in Jupyter notebook using Python on a Customer Satisfaction Data Set to explore, visualize, test, train and predict. Xgb boost
User: kwr4
Home Page: https://github.com/kwr4
classification-report,With the Student Alcohol Consumption data set, we predict high or low alcohol consumption of students.
User: manaliagarwal
classification-report,Understanding emotions from audio files using neural networks and multiple datasets.
User: marcogdepinto
classification-report,3 modelos de classificação para analisar churn de um empresa de telecom e ao final responder a pergunta: Qual modelo teve o melhor desempenho?
User: marlevek
classification-report,Evaluate Machine Learning Models with Yellowbrick
User: marwaeshra
classification-report,Python framework to evaluate Named Entity Recognition (NER) models. Creates entity-level confusion matrix and classification report.
User: mdadda
classification-report,predict where the patient will be discharged to before surgery
User: moggirain
classification-report,This is projects of Data Mining
User: mohammadtavakoli78
classification-report,The dataset is about past loans. The loan_train.csv data set includes details of 346 customers whose loans are already paid off or defaulted.
User: muhammadusmantipu
classification-report,Faces recognition example using eigenfaces and SVMs
User: nazanin1369
classification-report,Trained and evaluated two supervised machine learning models using original and resampled data to identify 'healthy loan' and 'high risk loan' applicants from financial disclosures.
User: neonostrich
classification-report,Tool demonstrating building credit risk models
User: pkiage
Home Page: https://huggingface.co/spaces/pkiage/credit_risk_modeling_demo
classification-report,The main purpose of our proposed method is used to predict the quality of water by using Machine Learning algorithm.
User: ramyadeveloper59
classification-report,Create a Logistic Regression model to predict the credit risk of customers to a lending company. Use historical data and train the model before making predictions of test data. Lastly write an analysis report on the models created.
User: rjbarker
classification-report,Engaged in research to help improve to boost text sentiment analysis using facial features from video using machine learning.
User: roshansridhar
classification-report,Conducted data analysis, statistical analysis, and data visualization on an Indian crime dataset. Applied various machine learning algorithms to gain insights from the data. Utilized Time-Series models for prediction and forecasting based on the crime data analysis.
User: sahilichake
classification-report,Given a set of text movie reviews that have been labeled positive or negative, a machine learning classification model should be trained and tested for predicting the nature of future movie reviews.
User: sainikhilp
Home Page: http://ai.stanford.edu/~amaas/data/sentiment/
classification-report,This repository contains introductory notebook for logistic regression
User: sanketmaneds
classification-report,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
User: sharmaroshan
classification-report,Credit risk is an inherently unbalanced classification problem, as the number of good loans easily outnumber the number of risky loans. I employed Machine Learning techniques to train and evaluate models with unbalanced classes. I used imbalanced-learn and scikit-learn libraries to build and evaluate models using resampling. I also evaluated the performance of these models and made a recommendation on whether they should be used to predict credit risk.
User: shaunwang1350
classification-report,:syringe: Vaccine Sentiment Classifier is a deep learning classifier trained on real world twitter data, that distinguishes 3 types of tweets: Neutral, Anti-vax & Pro-vax.
User: spchalk
classification-report,Water Quality Analysis
User: sridhar922
classification-report,Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images
User: sushantdhumak
classification-report,Artificial intelligence (AI, ML, DL) performance metrics implemented in Python
User: thieu1995
Home Page: https://permetrics.readthedocs.io/en/latest/
classification-report,Supervised machine learning to train and evaluate models based on loan risk.
User: tmard
classification-report,Supervised-ML-Decision-Tree-C5.0-Entropy-Iris-Flower-Using Entropy Criteria - Classification Model. Import Libraries and data set, EDA, Apply Label Encoding, Model Building - Building/Training Decision Tree Classifier (C5.0) using Entropy Criteria. Validation and Testing Decision Tree Classifier (C5.0) Model
User: vaitybharati
classification-report,Assignment on Logistic Regression
User: vibhuti03
classification-report,This repository features code for a fraud detection model achieving 100% accuracy in identifying fraudulent credit card transactions. Utilizing transaction data from Jan 2019 to Dec 2020, the model employs RandomForestClassifier, assessing features like credit card numbers, transaction amounts, and merchant information.
User: vishakha-33
classification-report,This repo is about Machine Learning and Classification
User: vmieres
classification-report,
User: zauverer
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.