xgboost-algorithm

There are 5 repositories under xgboost-algorithm topic.

susanli2016 / Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
linear-regression polynomial-regression logistic-regression decision-trees random-forest svm svr knn-classification naive-bayes-classifier kmeans-clustering hierarchical-clustering pca lda xgboost-algorithm
Language:Jupyter Notebook 4254
awesome-gradient-boosting-papers
benedekrozemberczki / awesome-gradient-boosting-papers
A curated list of gradient boosting research papers with implementations.
gradient-boosting gradient-boosting-classifier gradient-boosting-machine gradient-boosted-trees gradient-boosting-decision-trees xgboost xgboost-algorithm catboost lightgbm random-forest decision-tree classification-algorithm classification-trees machine-learning deep-learning h2o classifier classification-tree adaboost boosting
Language:Python 992
chasedehan / BoostARoota
A fast xgboost feature selection algorithm
machine-learning machine-learning-algorithms feature-selection xgboost-algorithm xgboost dimension-reduction algorithm boruta data-science datascientist datascience machinelearning
Language:Python 215
ldv1 / LinXGBoost
Extension of the awesome XGBoost to linear models at the leaves
xgboost-algorithm classification regression machine-learning-algorithms
Language:Python 77
jinlow / forust
A lightweight gradient boosted decision tree package.
ai machine-learning pyo3 python rust xgboost xgboost-algorithm
Language:Rust 56
KSpiliop / Fraud_Detection
Tuning XGBoost hyper-parameters with Simulated Annealing
xgboost xgboost-parameters hyperparameters fraud-detection tuning xgboost-algorithm
Language:Jupyter Notebook 51
ojasphansekar / Zillow-Home-Value-Prediction
XGBoost, LightGBM, LSTM, Linear Regression, Exploratory Data Analysis
python-3 machine-learning xgboost-algorithm lightgbm-models lstm-neural-networks exploratory-data-analysis data-preprocessing data-cleansing
Language:Jupyter Notebook 37
sauravmishra1710 / Heart-Failure-Condition-And-Survival-Analysis
Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.
healthcare-application healthcare-datasets machine-learning machine-learning-algorithms exploratory-data-analysis data-visualization lgbm xgboost-algorithm cardiovascular-diseases cox-regression heartfailure kaplan-meier-plot kaplanmeierfitter survival-analysis time-to-event
Language:Jupyter Notebook 37
farhanchoudhary / Machine_Learning_A-Z_All_Codes_and_Templates
All codes, both created and optimized for best results from the SuperDataScience Course
machine-learning-az classification neural-networks association-rule-learning clustering-algorithm xgboost-algorithm natural-language-processing naive-bayes-classifier dimensionality-reduction principal-component-analysis clustering grid-search k-fold cross-validation deep-learning reinforcement-learning thompson-sampling upper-confidence-bounds
Language:Python 33
vaishnavipatil29 / Career-Guidance-ML-Project
Career Guidance System Using Machine Learning Techniques
machine-learning decision-tree-classifier supportvectormachines xgboost-algorithm python careerguidance
Language:Jupyter Notebook 31
jaydipkumar / Data-Science-Python
Data Science Python Beginner Level Project
apriori-algorithm-python artificial-neural-networks convolutional-neural-networks decision-tree random-forest forecasting-models kmeans knn-algorithm nlp-machine-learning support-vector-machines xgboost-algorithm pca eclat-algorithm clustering-algorithm neural-network machine-learning-algorithms datascience machine-learning-projects machine-learning-tutorials machine-learning-projects-beginners
Language:Jupyter Notebook 29
fantasy-sports-prediction
pankajrawat9075 / fantasy-sports-prediction
We have used our skill of machine learning along with our passion for cricket to predict the performance of players in the upcoming matches using ML Algorithms like random-forest and XG Boost
xgboost-algorithm support-vector-machines random-forest dream11 python fantasy-sports final-year-project machine-learning
Language:Python 25
yogeshwaran-shanmuganathan / Airline-Passenger-Satisfaction
Determining the important factors that influences the customer or passenger satisfaction of an airlines using CRISP-DM methodology in Python and RapidMiner.
customer-satisfaction passenger-satisfaction factors airline-passengers airline-passenger-satisfaction python jupyter-notebook crisp-dm exploratory-data-analysis random-forest adaboost-classifier logistic-regression decision-tree-classifier xgboost-algorithm knn-classification naive-bayes-classifier rapidminer
Language:Jupyter Notebook 25
RudreshVeerkhare / CustomXGBoost
Modified XGBoost implementation from scratch with Numpy using Adam and RSMProp optimizers.
xgboost-algorithm numpy adam-optimizer rmsprop gradient-boosting-machine implementation-of-algorithms
Language:Jupyter Notebook 24
ali-ghorbani-k / Credit-Risk-Management
A binary classification model is developed to predict the probability of paying back a loan by an applicant. Customer previous loan journey was used to extract useful features using different strategies such as manual and automated feature engineering, and deep learning (CNN, RNN). Various machine learning algorithms such as Boosted algorithms (XGBoost, LightGBM, CatBoost) and Deep Neural Network are used to develop a binary classifier and their performances were compared.
lightgbm xgboost-algorithm catboost deep-learning
Language:Jupyter Notebook 19
eswar3 / Zillow-prediction-models
Machine Learning Project using Kaggle dataset
machine-learning xgboost-algorithm eda parameter-tuning scikit-learn scikitlearn-machine-learning numpy
Language:Jupyter Notebook 19
Hashehri / Network-Traffic-Classification-UNSW-NB15
Binary Classification for detecting intrusion network attacks. In order, to emphasize how a network packet with certain features may have the potentials to become a serious threat to the network.
machine-learning deep-learning network-analysis network-security ai sklearn xgboost-algorithm random-forest knn-classification decsion-tree pickle logistic-regression voting-classifier stacking-ensemble python3 classification-algorithims
Language:Jupyter Notebook 15
sohammanjrekar / Multiple-Disease-Prediction-Webapp
Designed web app employs the Streamlit Python library for frontend design and communicates with backend ML models to predict the probability of diseases. It's capable of predicting whether someone has Diabetes, Heart issues, Parkinson's, Liver conditions, Hepatitis, Jaundice, and more based on the provided symptoms, medical history, and results.
disease-prediction machine-learning python3 streamlit-webapp xgboost-algorithm
Language:Jupyter Notebook 10
Credit-Risk-Analysis
ankit-kothari / Credit-Risk-Analysis
Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods
ensembling-methods credit-risk-analysis xgboost-algorithm logistic-regression nueral-networks smote-sampling under-sampling boosting
Language:Jupyter Notebook 8
IshtyM / Shipping-Pricing-Prediction
Predicting the supply chain shipment pricing based on the available factors in the dataset using the classical machine learning algorithms.
machine-learning pandas python data-science data-analysis supply-chain regression xgboost-algorithm random-forest decision-trees
Language:Jupyter Notebook 8
KrishArul26 / Air-Quality-Index-prediction_with_deployment
India is one of the countries with the highest air pollution country. Generally, air pollution is assessed by PM value or air quality index value. For my further analysis, I have selected PM-2.5 value to determine the air quality prediction and the India-Bangalore region. Also, the data was collected through web scraping with the help of Beautiful Soup.
xgboost-algorithm svm-regressor hyperparameter-tuning linear-regression extra-trees-classifier rmse-score
Language:Jupyter Notebook 8
kush1912 / FAKE-NEWS-DETECTION
Machine learning Based Minor Project, which uses various classification Algorithms to classify the news into FAKE/REAL, on the basis of their Title and Body-Content. Data has been collected from 3 different sources and uses algorithms like Random Forest, SVM, Wordtovec and Logistic Regression. It gave 94% accuracy.
guardian webscraping machine-learning-algorithms svm classification-algorithm fake logistic-regression ipynb random-forest nyt scrap-data word2vec-model xgboost-algorithm
Language:Jupyter Notebook 8
Max-Q
MitchellTesla / Max-Q
Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing
neural-networks machine-learning-algorithms jupyter-notebooks python-3 arxiv-papers pytorch xgboost-algorithm xgboost-model xgboost-python xgboost-regression
Language:C++ 8
Mohsinrazaa / All-Machine-Learning-Algorithm
Machine Learning Assignments of inuroun academy ML with master deployment and deep learning 29th Aug. 2020
machine-learning deep-learning linear-regression logistic-regression knn decision-trees xgboost-algorithm random-forest classification clustering-algorithm
Language:Jupyter Notebook 8
omarmhaimdat / xgboost_student_performance
Introduction to XGBoost with an Implementation in an iOS Application
xgboost xgboost-algorithm xgboost-python coremltools ios-app ios-swift swift python machine-learning ensemble-machine-learning decision-tree-regression
Language:Swift 8
rishanki / Xgboost-VS-Catboost-Vs-LiteGBM
The python notebook is on googles new collabatory tool. Its a churn model being run on 3 different algorithms to compare.
xgboost-algorithm catboost gbm collaborative-editing machine-learning-algorithms churn-prediction telecommunications analytics
Language:Jupyter Notebook 8
govardhan26 / Parkinsons-Disease-Prediction
As an early diagnosis step machine learning classifiaction algorithms could be used in finding if the patient is prone to parkinsons disease.
machine-learning machine-learning-algorithms python jupyter-notebook classification parkinsons-disease crossvalidation xgboost-algorithm xgboost extratree blog blogs supervised-learning healthcare healthcare-application
Language:Jupyter Notebook 7
omerfarukeker / The-Complete-Journey
The Complete Journey Dataset: Churn Prediction
churn churn-prediction the-complete-journey-dataset dunnhumby xgboost xgboost-algorithm xgboost-model xgb-classifier hyperparameter-optimization feature-extraction feature-engineering
Language:Jupyter Notebook 7
rajatbansal01 / Machine_Learning-and-Data_Analysis
This repository contains various machine problems with solutions with various algorithms.
python3 machine-learning-algorithms sklearn knn-classification naive-bayes-classifier pca xgboost-algorithm svm-model hacktoberfest hacktoberfest2021 hacktoberfest-accepted
Language:Jupyter Notebook 7
susanli2016 / Machine-Learning-with-R
R codes for common Machine Learning Algorithms
linear-regression logistic-regression svr polynomial-regression decision-trees random-forest knn svm naive-bayes kmeans-clustering hierarchical-clustering apriori-algorithm pca lda xgboost-algorithm
Language:R 7
leonardodepaula / xgbimputer
Extreme Gradient Boost imputer for Machine Learning.
machine-learning missing-data missing-values missforest-imputation missforest scikit-learn xgboost xgboost-algorithm
Language:Python 6
TanerArslan / Benchmarking_Classifiers_after_SVM-RFE
Evaluating multiple classifiers after SVM-RFE (Support Vector Machine-Recursive Feature Elimination)
machine-learning svm-classifier random-forest logistic-regression lasso-regression xgboost-algorithm naive-bayes-classifier bagging-trees benchmarking object-oriented-programming python3 sklearn-library
Language:Python 6
a3X3k / Spam-Email-Detection
machine-learning python spam-classification machinelearning knn-classifier logistic-regression svm-classifier decision-tree-classifier random-forest-classifier naive-bayes-classifier gradient-boosting extratreesclassifier xgboost-algorithm bagging-ensemble adaboostclassifier knn-classification knn-model svm-kernel svm-model randomforestclassifier
5
datacrypto-analytics / crypto-analysis-cli
Analise todas as criptomoedas disponíveis na binance spot com algoritmos Machine Learning.
machine-learning xgboost matplotlib quantitative-finance cryptocurrency bitcoin ethereum binance binance-api binance-smart-chain machine-learning-algorithms xgboost-model xgboost-algorithm
Language:Python 5
g-aditi / customer-personality-analysis
Using a Kaggle dataset, customer personality was analysed on the basis of their spending habits, income, education, and family size. K-Means, XGBoost, and SHAP Analysis were performed.
machine-learning python kmeans-clustering kmeans xgboost xgboost-algorithm kmeans-clustering-algorithm xgboost-model shap-analysis shapley-additive-explanations customer-personality-analysis customer-personas
Language:Jupyter Notebook 5
sakusuma / CreditCardFraudDetection
Although digital transactions in India registered a 51% growth in 2018-19, their safety remains a concern. Fraudulent activities have increased severalfold, with around 52,304 cases of credit/debit card fraud reported in FY'19 alone. Due to this steep increase in banking frauds, it is the need of the hour to detect these fraudulent transactions in time in order to help consumers as well as banks, who are losing their credit worth each day. Machine learning can play a vital role in detecting fraudulent transactions. Imagine you get a call from your bank, and the customer care executive informs you that your card is about to expire in a week. Immediately, you check your card details and realise that it will expire in the next 8 days. Now, in order to renew your membership, the executive asks you to verify a few details such as your credit card number, the expiry date and the CVV number. Will you share these details with the executive? In such situations, you need to be careful because the details that you might share with them could grant them unhindered access to your credit card account.The aim of this project is to predict fraudulent credit card transactions using machine learning models. The data set that you will be working on during this project was obtained from Kaggle. It contains thousands of individual transactions that took place over a course of two days and their respective labels.
fraud-detection fraud-prevention regression logistic-regression decession-trees random-forest xgboost-algorithm xgboost knn-classification knn
Language:Jupyter Notebook 5

xgboost-algorithm

susanli2016 / Machine-Learning-with-Python

benedekrozemberczki / awesome-gradient-boosting-papers

chasedehan / BoostARoota

ldv1 / LinXGBoost

jinlow / forust

KSpiliop / Fraud_Detection

ojasphansekar / Zillow-Home-Value-Prediction

sauravmishra1710 / Heart-Failure-Condition-And-Survival-Analysis

farhanchoudhary / Machine_Learning_A-Z_All_Codes_and_Templates

vaishnavipatil29 / Career-Guidance-ML-Project

jaydipkumar / Data-Science-Python

pankajrawat9075 / fantasy-sports-prediction

yogeshwaran-shanmuganathan / Airline-Passenger-Satisfaction

RudreshVeerkhare / CustomXGBoost

ali-ghorbani-k / Credit-Risk-Management

eswar3 / Zillow-prediction-models

Hashehri / Network-Traffic-Classification-UNSW-NB15

sohammanjrekar / Multiple-Disease-Prediction-Webapp

ankit-kothari / Credit-Risk-Analysis

IshtyM / Shipping-Pricing-Prediction

KrishArul26 / Air-Quality-Index-prediction_with_deployment

kush1912 / FAKE-NEWS-DETECTION

MitchellTesla / Max-Q

Mohsinrazaa / All-Machine-Learning-Algorithm

omarmhaimdat / xgboost_student_performance

rishanki / Xgboost-VS-Catboost-Vs-LiteGBM

govardhan26 / Parkinsons-Disease-Prediction

omerfarukeker / The-Complete-Journey

rajatbansal01 / Machine_Learning-and-Data_Analysis

susanli2016 / Machine-Learning-with-R

leonardodepaula / xgbimputer

TanerArslan / Benchmarking_Classifiers_after_SVM-RFE

a3X3k / Spam-Email-Detection

datacrypto-analytics / crypto-analysis-cli

g-aditi / customer-personality-analysis

sakusuma / CreditCardFraudDetection