Predicting Sale Price of Houses

In this project, the dataset consisting of housing data with 81 features was preprocessed to select the top 30 features using Pearson correlation, Spearman correlation and, one-way ANOVA. The model was trained using Lasso Regression and Random Forest to achieve an accuracy of more than 80%.