Topic: xgboost-model Goto Github
Some thing interesting about xgboost-model
Some thing interesting about xgboost-model
xgboost-model,Forecasting Bitcoin Prices via ARIMA, XGBoost, Prophet, and LSTM models in Python
User: aaronflore
xgboost-model,Building a model to predict airbnb price and future occupancy bucket to estimate revenue for future investors
User: aarushi-vermaa
xgboost-model,A supervised classification machine learning approach to forecasting the road as safe (label 1) or dangerous (label 0) for driving in the arctic regions. If the friction is 0 <= x < 0.5 then we labeled it as 0, either 1 in the range 0.5 to 1.
User: abrar2652
xgboost-model,Web application for earthquake prediction in a window of few future days. live data collection from https://earthquake.usgs.gov/
User: aditya-167
xgboost-model,Building BigMart Sales Prediction
User: akash1070
xgboost-model,Personal Data Science Projects
User: alanchn31
xgboost-model,LiFePo4(LFP) Battery State of Charge (SOC) estimation from BMS raw data
User: alexdatadesign
xgboost-model, Find the best algorithm to analyze and predict the demand for cash withdrawals
User: anjalysam
xgboost-model, I'm attempting the NYC Taxi Duration prediction Kaggle challenge. I'll by using a combination of Pandas, Matplotlib, and XGBoost as python libraries to help me understand and analyze the taxi dataset that Kaggle provides. The goal will be to build a predictive model for taxi duration time. I'll also be using Google Colab as my jupyter notebook. i will also predict without Google colab on normal system.
User: ankitamd
xgboost-model,Data Mining Course Project - Diabetes Classification with XGBoost - Winter 2022
User: arminzolfaghari
xgboost-model, Crisis incidents caused by rebel groups create a negative influence on the political and economic situation of a country. However, information about rebel group activities has always been limited. Sometimes these groups do not take responsibility for their actions, sometimes they falsely claim responsibility for other rebel group’s actions. This has made identifying the rebel group responsible for a crisis incident a significant challenge. Project Floodlight aims to utilize different machine learning techniques to understand and analyze activity patterns of 17 major rebel groups in Asia (including Taliban, Islamic State, and Al Qaeda). It uses classification algorithms such as Random Forest and XGBoost to predict the rebel group responsible for organizing a crisis event based on 14 different characteristics including number of fatalities, location, event type, and actor influenced. The dataset used comes from the Armed Conflict Location & Event Data Project (ACLED) which is a disaggregated data collection, analysis and crisis mapping project. The dataset contains information on more than 78000 incidents caused by rebel groups that took place in Asia from 2017 to 2019. Roughly 48000 of these observations were randomly selected and used to develop and train the model. The final model had an accuracy score of 84% and an F1 Score of 82% on testing dataset of about 30000 new observations that the algorithm had never seen. The project was programmed using Object Oriented Programming in Python in order to make it scalable. Project Floodlight can be further expended to understand other crisis events in Asia and Africa such as protests, riots, or violence against women.
User: asaficontact
xgboost-model,Classifying audio files using ML algorithms.
User: ashcode028
xgboost-model,This is a Liver Disease Machine Learning Classification Capstone Project in fulfillment of the Udacity Azure ML Nanodegree. In this project, you will learn to deploy a machine learning model from scratch. The files and documentation with experiment instructions needed for replicating the project, is provided for you.
User: chollette
Home Page: https://github.com/chollette/Liver-Disease-Classification-Azure-ML-Capstone-Project
xgboost-model,COVID-19 Vulnerability Index
Organization: closedloop-ai
Home Page: http://cv19index.com
xgboost-model,Analise todas as criptomoedas disponíveis na binance spot com algoritmos Machine Learning.
Organization: datacrypto-analytics
Home Page: https://datacryptoanalytics.com/
xgboost-model,Exploratory and Predictive analysis of the Dota 2 dataset
User: dthrazak
xgboost-model,My solution for Quora's Question Pair contest on Kaggle.
User: dysdsyd
Home Page: https://www.kaggle.com/c/quora-question-pairs
xgboost-model,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.
User: g-aditi
xgboost-model,:octocat: Detection and Prediction of Air quality Index :octocat:
User: grtvishnu
xgboost-model,A credit card fraud detection algorithm.
User: harigovindv10
xgboost-model,
User: hutaf
xgboost-model,Data Science Experiments Repository of Ideas2IT
Organization: ideas2it
xgboost-model,Advance Time Series Analysis using Probabilistic Programming, Auto Regressive Neural Networks and XGBoost Regression.
User: javihaus
xgboost-model,Churn Modelling using XGBoost
User: jimschacko
xgboost-model,this is my repository for Amazon review helpfulness prediction model
User: keisukeirie
xgboost-model,this is my repository for the quick draw prediction model project
User: keisukeirie
xgboost-model,A simple mobile price prediction classifier
User: kshitij1210
xgboost-model,A host of data science + machine learning projects with Python, pandas, scikit-learn and more!
User: kyle-pu
xgboost-model,Machine learning model built for IBM Hack 2020 challenge. ⚙️
User: madhav-somanath
xgboost-model,Machine learning tutorial with examples
User: majd0507
xgboost-model,Multi-Objective Recommender System
User: mddunlap924
xgboost-model,使用比赛方提供的脱敏数据,进行客户信贷流失预测。
User: mstao-68
xgboost-model,# 自然语言处理 IMDB 情感分析数据集任务
User: mstao-68
xgboost-model,Project: What factors impact the accuracy of airfare prediction?
User: nickdcox
xgboost-model,World Health Organization has estimated 12 million deaths occur worldwide, every year due to Heart diseases. Half the deaths in the United States and other developed countries are due to cardio vascular diseases.
User: olaelshiekh
xgboost-model,The Complete Journey Dataset: Churn Prediction
User: omerfarukeker
xgboost-model,By using feature engineering technique and XGBoost algorithm to predict house price
User: pzugatti
xgboost-model,Data consists of tweets scrapped using Twitter API. Objective is sentiment labelling using a lexicon approach, performing text pre-processing (such as language detection, tokenisation, normalisation, vectorisation), building pipelines for text classification models for sentiment analysis, followed by explainability of the final classifier
User: rochitasundar
xgboost-model,Codes and templates for ML algorithms created, modified and optimized in Python and R.
User: rudrajit1729
xgboost-model,Implemented various ML algorithms with and without library functions. Final Project-->Application of LGBM, XGBoost, Catboost and SVC
User: sensudi
xgboost-model,Amazon Fine Food Reviews is classification Sentiment Analysis problem. Classify the positive and negative reviews given by Amazon users. Given some product-based features and related reviews in text data. Featuring data and apply various Machine Learning techniques to classify reviews.
User: shivamgupta7
xgboost-model,won silver medal, 164th of 5169
User: skyhuang1208
Home Page: https://www.kaggle.com/c/porto-seguro-safe-driver-prediction
xgboost-model,Machine learning models are used to determine whether a house is a good potential "flip" or not, using standard 70% rule.
User: stonecoldnicole
xgboost-model,Project work related to various hackathons
User: sujeeth-shetty
xgboost-model,Machine Learning on AWS using various methods/examples
User: sukeshreddy
xgboost-model,The project concerns an international e-commerce company* based in the USA who want to discover key insights from their customer database. They want to use some of the most advanced machine learning techniques to study their customers.
User: vishalv91
xgboost-model,Animal State Prediction Dataset
User: yashkim77
xgboost-model,Machine Learning to Determine Auto-Insurance Premiums using Telematics
User: yashmuchhala
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