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bagging-regressor

Here are 17 public repositories matching this topic...

Bagging is the term from "Bootstrap Aggregation Algorithm", That is for Low Bias & Low Variance

  • UpdatedDec 6, 2022
  • Jupyter Notebook

Analysis of flight systems to check the effectiveness of using Twitter data in conjunction with traditional datasets to improve predictions.

  • UpdatedJan 15, 2024
  • Jupyter Notebook

Goal is to predict the concrete compressive strength using collected data

  • UpdatedSep 7, 2020
  • Jupyter Notebook

Predicción del precio de venta de las viviendas en venta y de las viviendas en alquiler de Barcelona.

  • UpdatedApr 27, 2023
  • Jupyter Notebook

A Machine Learning exploration evaluating various models to predict Airbnb prices, culminating in an optimized Gradient Boosting Regressor.

  • UpdatedFeb 4, 2024
  • HTML

Developed a Health Insurance Premium Price Predictor using a dataset of personal attributes (age, gender, BMI, family size, smoking habits) to analyze their impact on medical insurance charges and predict healthcare costs.

  • UpdatedNov 27, 2024
  • HTML
  • UpdatedAug 8, 2024
  • Jupyter Notebook

This project provides the best possible price of a used car by taking attributes such as Manufactured Year, Number of Cylinders, Condition, and many more as inputs. Out of all models tested, the Random Forest model predicted the prices closest to the prices listed on Craigslist. Developed a web app using the Flask API for the deployment of this …

  • UpdatedMay 3, 2020
  • Jupyter Notebook

The dataset provides information on crop production in India from 1997 to 2015. The Crop Production was predicted using Decision Tree Regressor, K Neighbours Regressor, Bagging Regressor, Random Forest Regressor and Gradient Boosting Regressor

  • UpdatedAug 22, 2022
  • Jupyter Notebook

Predicting Compressive Strength of Concrete

  • UpdatedSep 19, 2022
  • Jupyter Notebook

This mini-project involves experimenting with a variety of classification and regression models, exploring different techniques to understand their behaviors and applications in predictive analytics.

  • UpdatedMay 2, 2022
  • Jupyter Notebook

Aim of this project is to predict taxi fare based on available data. This dataset contains total 8 variables and 50000 indexes.

  • UpdatedFeb 22, 2024
  • Jupyter Notebook

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