A linear regression model for house price prediction

Overview

Linear_Regression_Model

A linear regression model for house price prediction.

  1. This code is using these packages, so please make sure your have installed them:

    a. numpy
    b. pandas (please use the latest version: 1.3.3, lower version may cause some error)
    c. matplotlib

  2. If you found you have trouble with updating python or those packages, you can create anaconda environment to do so. Here is a link of the instruction to set up and use anaconda environment:

    https://stackoverflow.com/questions/28852841/install-anaconda-on-ubuntu-or-linux-via-command-line

    If use anaconda environment, you should use the following command to activate the anaconda environment:

    conda activate
    
  3. File description

    HousePrice_LinearRegression.py: The model file

    HousePrice_train.csv: The training set

    HousePrice_dev.csv: The validation set

    Competition_test.csv: The "real" data set, who has no correct prediction value

    Above are using files, so make sure to let them in the same directory, the code is using relative path.

    The rest of files, including those inside the folder "Figures" are generated by the code.

Owner
ShawnWang
ShawnWang
A Streamlit demo to interactively visualize Uber pickups in New York City

Streamlit Demo: Uber Pickups in New York City A Streamlit demo written in pure Python to interactively visualize Uber pickups in New York City. View t

Streamlit 230 Dec 28, 2022
Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Mert Sezer Ardal 1 Jan 31, 2022
Implementation of different ML Algorithms from scratch, written in Python 3.x

Implementation of different ML Algorithms from scratch, written in Python 3.x

Gautam J 393 Nov 29, 2022
A collection of machine learning examples and tutorials.

machine_learning_examples A collection of machine learning examples and tutorials.

LazyProgrammer.me 7.1k Jan 01, 2023
An AutoML survey focusing on practical systems.

This project is a community effort in constructing and maintaining an up-to-date beginner-friendly introduction to AutoML, focusing on practical systems. AutoML is a big field, and continues to grow

AutoGOAL 16 Aug 14, 2022
Simple data balancing baselines for worst-group-accuracy benchmarks.

BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating

Facebook Research 29 Dec 02, 2022
Machine learning template for projects based on sklearn library.

Machine learning template for projects based on sklearn library.

Janez Lapajne 17 Oct 28, 2022
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters

Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM

Joaquín Amat Rodrigo 297 Jan 09, 2023
Backtesting an algorithmic trading strategy using Machine Learning and Sentiment Analysis.

Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us

Renato Votto 31 Nov 17, 2022
A machine learning web application for binary classification using streamlit

Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas

abdelhak mokri 1 Dec 20, 2021
ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in

Computational Data Science Lab 182 Dec 31, 2022
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)

Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)

141 Dec 27, 2022
learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your personal portfolio

learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your

BDFD 6 Nov 05, 2022
Library for machine learning stacking generalization.

stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab

114 Jul 19, 2022
Optimal Randomized Canonical Correlation Analysis

ORCCA Optimal Randomized Canonical Correlation Analysis This project is for the python version of ORCCA algorithm. It depends on Numpy for matrix calc

Yinsong Wang 1 Nov 21, 2021
Machine Learning Algorithms

Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p

Göktuğ Ayar 3 Aug 10, 2022
This is a curated list of medical data for machine learning

Medical Data for Machine Learning This is a curated list of medical data for machine learning. This list is provided for informational purposes only,

Andrew L. Beam 5.4k Dec 26, 2022
PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors.

PyNNDescent PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors. It provides a python implementation of Nearest Neighbo

Leland McInnes 699 Jan 09, 2023
Distributed Evolutionary Algorithms in Python

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

Distributed Evolutionary Algorithms in Python 4.9k Jan 05, 2023
A quick reference guide to the most commonly used patterns and functions in PySpark SQL

Using PySpark we can process data from Hadoop HDFS, AWS S3, and many file systems. PySpark also is used to process real-time data using Streaming and

Sundar Ramamurthy 53 Dec 21, 2022