Topic: accuracy-score Goto Github
Some thing interesting about accuracy-score
Some thing interesting about accuracy-score
accuracy-score,This Project is based on Machine Learning which uses Logistic Regression model for predicting whether the object detected by Submarine is Rock or Mine
User: 4702chahat
accuracy-score,This code evaluates the performance of a logistic regression model on age prediction using various features to predict a binary target variable, calculating metrics to determine the performance. It evaluates the comparison, identifies favorable features, and visualizes the ROC-AUC curve to determine the best model performance.
User: aarryasutar
accuracy-score,evaluation metrics implementation in Python from scratch
User: ajitsingh98
Home Page: https://github.com/ajitsingh98/All-About-Performance-Metrics
accuracy-score,In this project, we aim to identify different fruits: apples, bananas, oranges, and tomatoes; through different Machine Learning algorithms: CNN, XGBoost, InceptionV3 transfer learning, and VGG16 transfer learning
User: anapysasi
accuracy-score,It calculates the accuracy score and confusion matrix for a logistic regression model. The dataset is about coupon used or not in an apparel store known as Simmons .
User: ashishyadav24092000
Home Page: https://github.com/ashishyadav24092000/Accuracy_confusionMAtrix_logisticRegression
accuracy-score,Crafted a machine learning model employing Support Vector Machine (SVM) algorithm to anticipate diabetes patterns using the diabetic prediction dataset. Dive into predictive analytics with this insightful project! ππ
User: bramitha-gowda-m
accuracy-score,Whack-a-mole mini-game where you whack viruses instead of moles.
User: dominicarrojado
Home Page: https://dominicarrojado.com/mouse-accuracy-game/
accuracy-score,Exploratory data analysis exercises to understand the main characteristics of a given data set before performing more advanced analysis or further modeling
User: doriandraper
Home Page: https://www.kaggle.com/competitions/titanic
accuracy-score,This repository contains all the Machine Learning projects I did using different Machine Learning methods. Python being the main software used.
User: e-paj
accuracy-score,Revolutionize customer feedback analysis with our NLP Insights Analyzer. Utilize cutting-edge text preprocessing to transform raw reviews into a machine-friendly format. Explore sentiment models, such as Logistic Regression and Naive Bayes, employing cross-validation for model robustness.
User: elmezianech
accuracy-score,This project develops an activity recognition model for a mobile fitness app using statistical analysis and machine learning. By processing smartphone sensor data, it extracts features to train models that accurately recognize user activities.
User: faezehabedi2023
accuracy-score,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
accuracy-score,This repository contains Machine Learning Classification algorithms implementation
User: gopika-s-nair
accuracy-score,Compared the metrics and performance of different classification algorithms on Heart Failure dataset from UCI ML Repository
User: grvnair
accuracy-score,Improving a Machine Learning Model
User: iamkirankumaryadav
accuracy-score,This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project
User: indrapaul824
accuracy-score,A Preprocessing, Analytical and Modeling Case Study using Supervised ML Models
User: indrapaul824
Home Page: https://colab.research.google.com/drive/1UTrU1NvRp34KTtOeugscTieXeD9aks07?usp=sharing
accuracy-score,To create a Decision Tree classifier and visualize it graphically, the purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.
User: jaanvig
accuracy-score,The purpose of this project is to develop and compare two machine learning models to detect spam emails. Spam detection is a crucial task in email filtering systems to protect users from unwanted and potentially harmful emails. The project involves using a dataset containing various features extracted from email content.
User: jmarihawkins
accuracy-score,Supervised Machine Learning and Credit Risk
User: keyoumao
accuracy-score,Machine Learning: Group Project
User: kk289
accuracy-score,Stock Price Prediction of APPLE Using Python
User: kk289
accuracy-score,I aim in this project to analyze the sentiment of tweets provided from the Sentiment140 dataset by developing a machine learning sentiment analysis model involving the use of classifiers. The performance of these classifiers is then evaluated using accuracy and F1 scores.
User: labrijisaad
accuracy-score,With the Student Alcohol Consumption data set, we predict high or low alcohol consumption of students.
User: manaliagarwal
accuracy-score,natural language processing techniques applied on hotel review dataset
User: manishsreerangam
accuracy-score,It's a Python based Movie Recommendation System, which recommends movies to the users based on the similarity to previously watched movies. I have solved a machine learning classification problem and evaluated the model's performance using confusion matrix, accuracy score, recall score, precision and f1 score.
User: mariyamsoffice
accuracy-score,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
accuracy-score,The model should predict whether is it going to rain the next day coming or it isn't. The models that have been deployed were TensorFlow Sequential, Random Forest Classifier and GradientBoostingClassifier. The best model on both training and test set was achieved with Gradient Boosting Classifier with 95.2% and 85.5% accuracy on the train and test.
User: marya80
accuracy-score,learning python day 6
User: maryamsoftdev
accuracy-score,Learning python day 4
User: maryamsoftdev
accuracy-score,Predicting house price
User: masihsoniya
accuracy-score,Here are some fun projects to learn ML using Handson approach
User: mathurshab2210
accuracy-score,Data analysis on Automobile Dataset
User: mboejua
accuracy-score,Women's clothing Reviews dataset. Exploratory data analysis of various attributes of dataset is performed.https://www.kaggle.com/nicapotato/womens-ecommerce-clothing-reviews
User: meena-shankar
accuracy-score,Kaggle competition-Titanic dataset(Prediction of Number of survivors in Titanic disaster)
User: mohamedfarhun
Home Page: https://www.kaggle.com/mohamedfarhunm/titanic-dataset-logreg/edit
accuracy-score,* Basis EDA * Handling Null/Missing Values * Handling Outliers * Handling Skewness * Handling Categorical Features * Data Normalization and Scaling * Feature Engineering *Accuracy score *Confusion matrix *Classification report
User: poojap-atil
accuracy-score,In this project we have created a spam classifier model on UCI dataset. We performed data cleaning and preprocessing, followed by Stemming and Bag of Words technique and finally developed a Naive Bayes Multinomial model.
User: prankur16shukla
accuracy-score,Covid-19 prediction (For Nepal) with different MODELS (Sigmoidal, Linear Regressor, Random Forest Regressor) and comparisons
User: sbmagar
accuracy-score,This Github repository contains projects related to prediction with Decision Tree. Exploring Insights/Inferences by performing EDA on the given project data (Iphone purchase).
User: shipra-09
accuracy-score,This Github repository contains projects related to Logistic regression. Exploring Insights/Inferences by performing EDA on the given project data (Bank Term deposit).
User: shipra-09
accuracy-score,This Github repository contains cross selling of health insurance customers on vehicle insurance product. We have to predict whether a customer would be interested in Vehicle Insurance or not by building a ML model. Exploring Insights/Inferences by performing EDA on the given project data. Finding the high accuracy
User: shipra-09
accuracy-score,This project develops a deep learning model that trains on 1.6 million tweets for sentiment analysis to classify any new tweet as either being positive or negative.
User: shubhambhatia2103
accuracy-score,Predicting credit risk with machine learning algorithms and help financial institutions detect anomalies, reduce risk cases, monitor portfolios with statistical functions.
User: simewl8
accuracy-score,This github repositiory contains the Flight Price Prediction project aims to develop a machine learning model to predict flight ticket prices based on various factors such as departure and arrival locations, dates, airlines, and other relevant features.
User: simran2911
accuracy-score,[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-score,Here we are trying to predict the closing price of the particular Netflix stock on a given trading day.
User: subhajeet-das
accuracy-score,π¨βπ»π¨βπ» Bank deposit prediction model by Binomial Logistic Regression
User: sumankolkata
accuracy-score,This performs of evaluation of machine learning models with ease and provides the visualization
User: tech-amol5278
accuracy-score,This Model is used to Predict Emails data. Either emails are Spam or Normal (Ham) Mail.
User: umarrajpoot
accuracy-score,This dataset was used to learn more about how some machine learning models work: KNN, Naive Bayes, and Decision Tree. It also includes some model evaluation metrics: Precision, Recall, Accuracy, and F1-Score. These metrics were derived from the confusion matrix.
User: warpedro1
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