/Boston-House-Price-Prediction-Using-Random-Forest-Regression

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Boston-House-Price-Prediction-Using-Random-Forest-Regression

  • This is a machine learning model made using python and flask which predicts the price of boston house using Random Forest Regression Algorithm.
  • Do ⭐ the repository, if it helped you in anyway.

About the Dataset :

  • A Dataset derived from information collected by the U.S. Census Service concerning housing in the area of Boston Mass. This dataset contains information collected by the U.S Census Service concerning housing in the area of Boston Mass.
  • In this dataset made for predicting the Boston House Price Prediction. Here I just show the all of the feature for each house separately. Such as Crime rate of the House’s Area and so on.

Dependencies:

  • Python - 3.6
  • Scikit-Learn
  • Pandas
  • Numpy
  • Matplotlib
  • Seaborn
  • Pickle
  • Flask
  • Plotly

Algorithms Used:

  • RandomForestRegressor
  • GridSearchCV
  • train_test_split
  • chi2 and modelSelection

A glimpse of the web app:

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Team Members