Topic: catboostregressor Goto Github
Some thing interesting about catboostregressor
Some thing interesting about catboostregressor
catboostregressor,Sales prediction and data enrichment using Catboost and Upgini.
User: 1391819
Home Page: https://www.kaggle.com/code/robertonacu/sales-forecasting
catboostregressor,Trains, tunes, and evaluates different regression models to develop a time-efficient, high-quality model for predicting car prices based on RMSE and CPU runtime.
User: adkwn1
catboostregressor,Student performance
User: amruta33
catboostregressor,Prediction of the sale price of a vehicle using predictive models using gradient boosting
User: angelicavelez
catboostregressor,A simple data science project that involves web scraping, data cleaning and visualization, model building, and model explanation using character data from Marvel Fandom.
User: arnelmalubay
catboostregressor,Use regression techniques to predict the number of times a news article will be shared online
User: bchryzal
catboostregressor,
User: bicerinka
catboostregressor,Example machine learning applications for the determination of the residual yield force of corroded steel bars tested under monotonic tensile loading. Data is collected from 26 experimental programs avaialbe in the literature.
User: bma114
catboostregressor,A Predictive analysis project to predict the success rate of On-Time deposits of Premiums by Policy Holders.
User: chitranjan806
catboostregressor,Regression model that predicts demand for bicycle rentals
User: dashnak90
catboostregressor,A python script for basic data cleaning/manipulation and modelling based on the open source House Sales Advanced Regression Techniques(Kaggle)
User: dtheod
catboostregressor,This project focuses on developing a Machine Learning model to predict housing prices in California.
User: enescatagan
catboostregressor,This repository will work around solving the problem of food demand forecasting using machine learning.
User: erdos1729
catboostregressor,๐บ CatBoost Model Per Family
User: ggeop
catboostregressor,PlayerUnknownโs Battlegrounds (PUBG) is a popular battle royale game where players compete against each other in a last-person-standing format. Winning a match requires a combination of skill, strategy, and luck. In this project, we aim to predict the likelihood of winning a PUBG match based on various in-game features.
User: gopalkholade
catboostregressor,Telecom Customer Churn Prediction with 9 Different Alghoritms
User: haluksumen
catboostregressor,Machine Learning model to predict the weekly dispatch count of the warehouse.
User: hariprasath-v
catboostregressor,Build a machine learning model that predicts the Envision Racing driversโ lap times.
User: hariprasath-v
catboostregressor,YouTube View Count and Viewers Analysis Model
User: harshit-sinha-49
catboostregressor,Analytic Vidhya's Problem Statement to Predict or Forecast the Future Energy Demand For Next Three Years.
User: iamsj2022
catboostregressor,Time series forecasting on power consumption pattern with Catboost and regression model
User: issacchan26
catboostregressor,Machine Learning Regression Problem: Predicting the Car Orders Price (IDR) given car orders dataset
User: jeftaadriel
Home Page: https://www.kaggle.com/competitions/ristek-data-competition/overview
catboostregressor,Machine Learning Regression Problem: Predicting the CO2 Emission (g/km) given four wheel vehicle dataset
User: jeftaadriel
Home Page: https://www.kaggle.com/competitions/penyisihan-mlc-data-slayer-2023/overview
catboostregressor,To develop a machine learning model that accurately predicts housing prices using the Boston Housing dataset by analyzing various house features, and it utilizes a CatBoost model to assist potential buyers or sellers in estimating housing prices.
User: kalyanm45
catboostregressor,Interpreting wealth distribution via poverty map inference using multimodal data
User: lisette-espin
Home Page: https://vis.csh.ac.at/poverty-maps/
catboostregressor,Production prediction is one of the core problems in a company. The provided dataset is a set of nearby wells located in the United States and their 12 months cumulative production. The company data scientist needs to build a model from scratch to predict production.
User: m4theus4ndr4de
catboostregressor,CatBoost regressor for Predicting alcohol level based on chemical properties of the white wine
User: marguna23
Home Page: https://www.loom.com/share/c264a36862a6411a8599b3e3b0d126ba?sid=0d4b2be4-dd11-435e-afe0-e176458a23df
catboostregressor,The goal of the challenge is to predict, based on the analysis of the correlation of a year of consumption and weather training data, the electricity consumption of two given sites for a test year.
User: me-hdi
catboostregressor,Car price dataset analysis and modeling using catboost regressor
User: mehrabkalantary
catboostregressor,Accident damage prediction using catboost regressor
User: mehrabkalantary
catboostregressor,House price estimation from visual and textual features using both machine learning and deep learning models
User: mehrabkalantary
catboostregressor,Predict precipitation to mitigate flood damage in Bangladesh
User: mihorosenberg
Home Page: https://bangladesh-flood-guard-k65x4wbqyaykvbgf8jyunl.streamlit.app/
catboostregressor,You are provided hourly rental data along with weather data. For this competition, the training set is comprised of the first 20 days of each month, while the test set is the 21th to the end of the month. You must predict the total count of bikes rented during each hour covered by the test set, using only information available prior to the rental period.
User: mohamedsalman-git
catboostregressor,This application is based on a CatBoost machine learning model. This basically takes four queries from the user (Upazila/Thana name, Network availability (3G/4G), District, and Zip code) and outputs the best operator for that location. This model was trained on the data I collected from Opensingnal application. I collected 22,360 data for 559 locations of Bangladesh. Currently this model is based on a static dataset but in the future, I have a plan to upgrade it to a real-time data collection-based model.
User: mushfiqur-rahman-robin
catboostregressor,Developed a multi-class classification model to identify and classify faults according to specified categories. The model can be used to flag a device returning faulty data automatically.
User: ndabdulsalaam
Home Page: https://ndabdulsalaam.github.io/
catboostregressor,API files for Stutern inter-track-webapp for rent prediction.
User: ndcharles
catboostregressor,Predictive Uncertainty in Gradient-Boosted Regression Trees : A Muon Energy Reconstruction Case Study
User: nickarafyllis
catboostregressor,Model that uses 10 different algorithms to predict the revenue of a movie before it's release
User: permanatayev
catboostregressor,JOB-A-THON - January 2023
User: pratikdavidson
catboostregressor,In this project I have implemented 15 different types of regression algorithms including Linear Regression, KNN Regressor, Decision Tree Regressor, RandomForest Regressor, XGBoost, CatBoost., LightGBM, etc. Along with it I have also performed Hyper Paramter Optimization & Cross Validation.
User: praveenobulreddy
catboostregressor,House Rate Predictor
User: sineme01
catboostregressor,Delivery Pickup Analysis and Duration Prediction for Deliveries on Redis Graph using OSRM and CatBoost Regressor
User: slcnyagmurnew
catboostregressor,A web app to predict fare for some indian flights. An end-to-end machine learning project.
User: thebemer
Home Page: https://predict-indianflightprice.herokuapp.com/
catboostregressor,Kaggle LANL Earthquake Prediction challenge, Genetic Algorithm (DEAP) + CatboostRegressor, private score 2.425 (31 place)
User: viktorsapozhok
Home Page: https://viktorsapozhok.github.io/deap-genetic-algorithm/
catboostregressor,Housing sale price prediction using linear regression, Ridge, KNN, Catboost and XGBoost
User: wamae
catboostregressor,2022-01 ๋ฐ์ดํฐ๋ง์ด๋์ด๋ก ๋ฐ์์ฉ ํ๋ก์ ํธ <์ฅ์ ์ธ ์ด๋๊ถ ์ ๊ณ ๋ฅผ ์ํ ์ฝํ์ ์ด์ฉํธ์ ์ฆ์ง ๋ฐฉ์ : ์์ธํน๋ณ์๋ฅผ ์ค์ฌ์ผ๋ก>
User: yoojin730
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