Simple linear regression excel how to#
Simple linear regression excel code#

In this blog post, we compiled a diverse list of 15 datasets (CSV, Excel) suitable for training and practicing linear regression models. # Replace 'feature_columns' and 'target_column' with appropriate column namesįeature_columns = However, if the file is downloaded to your local drive, you may try with the following Python code:

Simple linear regression excel code#

The above code can be used as it is to read CSV files from URL and train the linear regression models. X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) # Split the dataset into training and testing sets # Separate the features (X) and target (y) The following Python code snippet imports the necessary libraries, loads the Boston Housing Dataset, splits the data into training and testing sets, trains a linear regression model, makes predictions on the test set, and calculates the performance metrics (Mean Squared Error, Root Mean Squared Error, and R-squared) to evaluate the model’s performance.įrom sklearn.model_selection import train_test_splitįrom sklearn.linear_model import LinearRegressionįrom trics import mean_squared_error, r2_score

Simple linear regression excel how to#

The following is a sample Python code snippet demonstrating how to train a linear regression model using the Boston Housing Dataset.

Python Code for Training Linear Regression Models using CSV Dataset Description: Predicting the burned area of forest fires based on meteorological data.Description: Predicting graduate admission chance based on various factors.Description: Predicting bike rental count based on time and weather factors.Description: Predicting student performance based on demographic and school-related factors.Description: Predicting abalone age based on physical measurements.Description: Predicting global video game sales based on platform, genre, etc.Description: Predicting energy consumption of appliances and lights based on various factors.Description: Predicting concrete compressive strength based on its ingredients.Description: Predicting disease progression based on diagnostic measurements.Description: Predicting house prices based on real estate features.

Description: Predicting sales based on advertising channels.Description: Predicting wine quality based on physicochemical properties.Description: Predicting medical costs based on patient information.Description: Predicting fuel efficiency (MPG) of cars based on 7 features.Description: Predicting house prices based on 13 features.The following is a list of 15 dataset which you can use to train linear regression models for learning purpose: List of Dataset for Training Linear Regression Models Python Code for Training Linear Regression Models using CSV Dataset.List of Dataset for Training Linear Regression Models.